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Table of Contents (click to follow link) CURRICULUM VITAE ............................................................................................................... 3 Professional Preparation ..................................................................................................... 3 Appointments ...................................................................................................................... 3 Professional Registration .................................................................................................... 3 Awards and Honors ............................................................................................................. 4 RESEARCH .............................................................................................................................. 4 Areas of Research Specialization ........................................................................................ 4 Research Contracts and Grants ........................................................................................... 4 Refereed Journal Publications ........................................................................................... 11 Refereed Conference Papers (full paper reviewed)........................................................... 14 Other Significant Peer Reviewed Publications ................................................................. 15 Refereed Conference Papers (full papers, abstract reviewed) ........................................... 15 Technical Reports, Software and Archival Datasets ......................................................... 18 Oral Presentations ............................................................................................................. 22 Impact of Research ............................................................................................................ 29 Professional Development Activities ................................................................................ 31 TEACHING ............................................................................................................................ 32 Courses Taught ................................................................................................................. 32 PH.D. Supervision ............................................................................................................ 33 M.S. Supervision .............................................................................................................. 34 Student Advisees’ Major Awards ..................................................................................... 36 SERVICE ................................................................................................................................ 37 Society Membership ......................................................................................................... 37 Current Professional Society Leadership and Committees ............................................... 37 Previous Professional Service ........................................................................................... 37 Reviewer ........................................................................................................................... 39 University Service ............................................................................................................ 40 Workshops, Seminars and Training Sessions ................................................................... 42 TEACHING PORTFOLIO ........................................................................................................ 43 Teaching Philosophy ............................................................................................................... 44 Delivery of Material ................................................................................................................ 44 Evaluation of Student Learning ............................................................................................. 44 Course Evaluation .................................................................................................................. 44 Sample Student Testimonials .................................................................................................. 46 RESEARCH PORTFOLIO ....................................................................................................... 48 Research Interests ................................................................................................................... 49 Current and Future Research ................................................................................................... 49 Exhibit A - Candidate Plan for Endowed Position Funding Investments ............................... 53 Sample of Work – Exhibit B .........................................................................................57 Sample of Work – Exhibit C ....................................................................................................... Sample of Work – Exhibit D ...................................................................................................... Sample of Work – Exhibit E .......................................................................................................

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Reginald R. (Reg) Souleyrette, Ph.D., P.E

CURRICULUM VITAE .

Gerald and Audrey Olson Professor of Civil Engineering 328 Town Engineering Dept. of Civil, Constr. and Environmental Engineering (CCEE) Ames, Iowa 50011 Institute for Transportation Phone: (515) 294-5453 Iowa State University Email: reg@iastate.edu Fax: (515) 294-0467

PROFESSIONAL PREPARATION

University of California, Berkeley Berkeley, CA

Civil Engineering - Transportation

Ph.D., May 1989

University of Texas at Austin Austin, TX

Civil Engineering - Transportation

MSCE, May 1986

University of Texas at Austin Austin, TX

Civil Engineering BSCE, December 1984

APPOINTMENTS

Gerald and Audrey Olson Professor 2005 - present Associate Director, Center for Transportation Research and Education (CTRE); Research Director, Midwest Transportation Consortium, Institute for Transportation

May 1993 - present

Professor of Civil Engineering 2003 - 2005 Associate Professor of Civil Engineering 1996-2003 Assistant Professor of Civil Engineering, Iowa State University 1993-1996 Assistant Professor of Civil Engineering and Assistant Director, TRC, University of Nevada, Las Vegas

1989-1993

Research & Teaching Assistant University of Texas at Austin

1986-1989

Graduate Engineer Intern Peat Marwick Main Airport Planners

1987

Research & Teaching Assistant University of Texas at Austin

1985-1986

Graduate Engineering Intern WHM Traffic Consultants

1985-1986

Surveying, Materials and Traffic Technician Texas DOT

1982-1984

Coop Student Woodward Clyde Geotechnical Engineers

1981

PROFESSIONAL REGISTRATION

Professional Engineer License, No. 14662, State of Iowa, 1999.

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AWARDS AND HONORS

• Engineering Student Council Leadership Award, February, 2008. • National Roadway Safety Award, “Iowa 's Local Roads Safety Initiatives,” US Dept of

Transportation, August, 2007 (team award) • Engineering Student Council Leadership Award, January, 2006. • Gerald and Audrey Olson Professorship, November, 2004. • Engineering Student Council Leadership Award, February, 2003. • National Safety Council, 28th International Traffic Records Forum Best Practices Honorable

Mention, Iowa’s Emergency Response Information System, 2002. • Joseph and Elizabeth Anderlik Award for Excellence in Undergraduate Teaching, 2001. • Iowa DPS Commissioner’s Special Award for Traffic Safety, 2001. • National Safety Council, 26th International Traffic Records Forum Best Practices Award Iowa

National Model/Crash Location Software Development, 2000. • Hammer Award, Vice President’s National Partnership for Reinventing Government (Iowa National

Model/Crash Location Software Development), 2000. • Charles W. Schaefer Award for Excellence in Teaching, Research and Service, 1998. • Distinguished Lecturer, Mid-America Transportation Center, April 1998. • Governor’s Volunteer Award for Outstanding Service to the State of Iowa, 1998. • American Society for Engineering Education Centennial Award, 1993. • ASEE, Dow Chemical Corporation Outstanding Young Faculty Award, PSW Section, 1992. • Regents of the University of Nevada System Outstanding Faculty Award, 1991. • Sigma Xi, Scientific Research Society, 1991. • Outstanding Graduate Student Instructor, University of California, Berkeley, 1987. • Industrial Liaison Program Scholarship, University of California, Berkeley, 1986. • Institute of Transportation Engineers (ITE) District 5 Best Student Paper Award, 1986. • Eno Foundation for Transportation Fellowship, University of Texas, 1985. • Tau Beta Pi, 1983. • Chi Epsilon, 1983. • Ernest Cockrell Jr. Scholarship, University of Texas, 1980-1984.

*** RESEARCH***

AREAS OF RESEARCH SPECIALIZATION

• Geospatial information Systems • Traffic Safety • Planning Models • Remote Monitoring and Sensing

RESEARCH CONTRACTS AND GRANTS Note: responsible for $9.2M, $8.1M as P.I., $1.1 of $5.5 as co-PI; lead or sole PI unless otherwise indicated; some cost-extended projects listed as multiple projects if more than one phase.

159. “MiniSim Mobile Lab (driver simulator),” Iowa State U. and U. of Iowa), 5/10-10/10 .............. $61,127 158. “Iowa Traffic Safety Data Service (ITSDS): Year 11,” Iowa Governor’s Traffic Safety Bureau (GTSB), 10/09-9/10 ............................................................................................. $178,200 157. Enhancements to the Iowa DOT CMAT Software, Iowa DOT, 2010 ........................................... $21,298

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156. Web-based Incident Location Tool, Iowa DOT, 2010 .................................................................. $99,995 155. Roundabout Screening Tool and Analysis, Iowa DOT, 2010 ....................................................... $30,695 154. Driver Simulator J-turn Simulation and CAD Conversion, Iowa DOT, 2010 ............................... $60,674 153. J-Turn Simulation and Conflict Analysis, MTC, 2010.................................................................. $20,000 152. Road Protection Scoring for Small Metro Area Safety Planning, MTC, 2010 ............................. $20,000 151. Identification and Measurement of High Crash Curves, MTC/Iowa DOT, 2010 ......................... $41,668 150. Crash Analysis Research Needs, Minnesota Dept. of Transportation, 2010 ................................. $27,706 149. Co-PI (15%) SHRP-2 S04A: Roadway Information Database Development and Technical

Coordination and Quality Assurance of the Mobile Data Collection Project (S04B), National Academies TRB Strategic Highway Research Program 2, 2010-2014 ........................ $1,000,000

148. “Iowa Traffic Safety Data Service (ITSDS): Year 11,” Iowa Governor’s Traffic Safety Bureau (GTSB), 10/09-9/10 ............................................................................................. $142,560 147.co-P.I. (30%) “Incorporating Safety in Small Area Planning Studies,” City of Ames and

Iowa DOT, 3/09-6/11 ..................................................................................................................... $80,000 146.co-P.I. (10%) “Midwest Transportation Consortium,” USDOT RITA, 10/09-9/10 ..................... $926,700 145. “Iowa Comprehensive Statewide Safety Plan Safety Analysis,” Iowa DOT, 6/09-1/11 ............. $102,617 144. “Alternative Strategies for Safety Improvement Investments,” TRB’s National

Cooperative Highway Research Program, (original PI Tom Maze), 12/08-8/09 .......................... $19,120 143. “Management of Rural Expressways,” Iowa DOT (original PI Tom Maze), 5/07-12/10 ............. $75,000 142. “ITSDS: Year 10,” GTSB, 10/08-9/09 ....................................................................................... $142,560 141. “Safety Analysis Coordination,” Iowa DOT, 8/08-6/09 ................................................................. $16,688 140. Co-P.I. (20%), “Development of a Device for Analysis of Portland Cement Concrete and Composite Pavements,” Iowa DOT Pooled Fund (with FHWA), 11/06-3/08 ........................ $80,000 139. Co-P.I. (20%), “Student Programmer Support,” Iowa DOT, 7/07-6/08 ....................................... $179,712 138. “Safety Data Workshops,” FHWA (through SAIC), 9/07-6/11 .................................................... $37,097 137. “State Traffic Safety Engineers List Serve,” FHWA, 5/06-3/09 ................................................... $15,834 136. “US Road Assessment Program Outreach,” U.S. DOT Midwest Transportation

Consortium (MTC), 10/07-9/10 ................................................................................................. $168,108 135. “Safety Analysis of Low Volume Rural Roads in Iowa,” Iowa DOT, 11/07-6/09 ........................ $34,969 134. “Crash Mapping and Analysis Tool Revisions,” Minn. DOT, 2/07-5/07 ...................................... $19,980 133. “Geospatial Safety Analysis,” Iowa DOT, 6/07-6/09 ..................................................................... $30,400 132. “ITSDS: Year 9,” GTSB, 10/07-9/08 ......................................................................................... $142,560 131. “Florida Location Tool modifications,” Iowa DOT, 6/05-3/06 ..................................................... $19,996 130. “Revision of Crash Mapping and Analysis Tool,” Iowa DOT, 3/06-5/06 ................................... $17,000 129. “IMAT Feature Revisions,” Iowa DOT, May 2007 – May 2008 .................................................. $42,000 128. “Minnesota DOT Crash Mapping and Analysis Tool,” Minn. DOT, 10/05-4/06 ......................... $57,000 127. Co-P.I. (20%), “Student Programmer Support,” Iowa DOT, 7/06 – 6/07 ................................... $179,157 126. Co-P.I. (50%), “CICAS Cost Benefit Analysis Tool,” FHWA/SAIC, 5/06-12/07 ........................ $30,958 125. Co-P.I. (20%), “Workzone Forecasting,” Midwest Smart Workzone Init., 7/06-6/11 .................. $51,821 124. “Safety Data Evaluation,” FHWA (through SAIC), 10/06-9/08 ................................................... $21,032 123. “Workzone Channelization,” Midwest Smart Workzone Initiative, 7/06-6/07 ............................. $40,587

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122. “Law Enforcement Safety Liaison, FFY 07,” GTSB, 10/06-9/07 ................................................. $70,000 121. “ITSDS: Year 8,” GTSB, 10/06-9/07 ......................................................................................... $124,460 120. “Evaluation of Iowa’s 70mph Speed Limit,” Iowa DOT, 5/06-12/10 ............................................ $73,650 119. “Validating Crash records,” Iowa DOT, 5/06-12/06 ...................................................................... $20,000 118. “Incident Location Tool Rewrite,” Iowa DOT, 5/06-9/10 ........................................................... $259,907 117. “Incident Location Tool: Support for TraCS Agencies,” Iowa DOT, 5/06-9/10 ........................ $108,556 116. Co-P.I. (20%), “State Trans. Plan Update Assistance,” Iowa DOT, 12/05-11/06........................ $100,000 115. “ITSDS and SMS Strategic HW Safety Plan Support,” Iowa DOT, 5/05-6/11 ........................... $197,500 114. “High-speed Expressway Intersections Crash Risk Factors,” Iowa DOT, 11/05-6/08 .................. $50,000 113. “Weatherview: XML Data Structure & Maintenance,” Iowa DOT, 7/05-12/08............................ $60,592 112. “Law Enforcement Safety Liaison, FFY 06,” GTSB, 10/05-9/06 .................................................. $70,000 111. Co-P.I. (10%), “Planning, Implementation and Operation of the Iowa Pavement Mgmt Program (IPMP): Phase 11,” Iowa DOT, August 2005 – December 2006 ....................... $168,200 110. Co-P.I. (15%), “Implementation of the Iowa DOT Pavement Management Optimization Model (PMOM) – Phase 11,” Iowa DOT, August 2005 – July 2006 ........................................... $30,375 109. “Incident Location Tool Support for Delaware State Police,” Iowa DOT, 2/05-5/05 ................... $9,994 108. “Incident Mapping Analysis Tool: Oracle Database Interface,” Iowa DOT, 3/05-8/05 ................. $4,998 107. “Software Revision for Crash Mapping and Analysis Tool,” Iowa DOT, 1/04-12/04 .................. $25,583 106. “ITSDS: Year 6,” GTSB, October 2004-September 2005 ............................................................ $66,570 105. “Statistical Analysis of Four Lane to Three Lane Conversion,” Iowa DOT, 1/05-6/05 ................ $10,000 104. “Student Support for Systems Planning Office,” Iowa DOT, 12/04-12/05 .................................... $19,827 103. co-P.I. (25%), “Development of a New Process for Determining Design Year Traffic Demands,” Iowa Highway Research Board (IHRB), January 2005-February 2007 ................... $125,000 102. “Guidelines for Removal of Unwarranted Traffic Control Devices in Rural Areas,” IHRB, November 2004-October 2005 ........................................................................................... $77,000 101. “US Road Assessment Program,” AAA Foundation for Highway Safety through Midwest

Research institute, May 2004-January, 2011................................................................................ $422,402 100. “Incident Mapping and Analysis Tool,” New York State Police, 6/04-2/05 ................................. $74,852 99. “Law Enforcement Safety Liaison, FFY 05,” GTSB, 10/04-9/05 .................................................. $67,500 98. “Telephone Support for Incident Location Tool,” Iowa DOT, August 2004-June 2005 ................. $15,000 97. co-P.I. (50%), “Law Enforcement Safety Liaison, FFY 04,” GTSB, 10/03-9/04 ............................ $65,340 96. “Revision of GIS-Based Incident Location Tool, Phases 9-12” Iowa DOT, 7/03-9/10 ................. $128,100 95. “Incident Location Tool Support for North Dakota Department of Transportation,” Iowa DOT, October 2004-March 2005 ........................................................................................... $20,000 94. Co-P.I. (20%), “Subarea Model,” City of West Des Moines, 10/03-4/04 ...................................... $86,600 93. “ITSDS: Year 5,” GTSB, October 2003-September 2004 .............................................................. $75,000 92. “Traffic Monitoring Program Planning with Remote Sensing,” Iowa DOT, 5/03-5/04 .................. $27,500 91. “Incident Location Tool for Florida,” Florida State University, 9/03-11/03 ................................... $14,864 90. “Incident Location Tool for South Dakota,” South Dakota DOT, 8/03-1/04 .................................. $49,731 89. “Crash Mapping and Analysis Tools: Traffic and Criminal Software interface

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Framework (IMAT),” Iowa DOT, April 2003-September 2004 ..................................................... $35,173 88. “'Effectiveness of All Red Clearance Time on Intersection Accidents and Violation Trends,” Minnesota DOT Local Roads Research Board, May 2003 – February 2004 ................... $49,978 87. “Incident Location Tool for Delaware,” Delaware DPS, 10/02-3/03 ............................................... $49,107 86. “ITSDS: Year 4,” GTSB, October 2002-September 2003 ............................................................... $75,000 85. “Vendor Weather Forecast,” Iowa DOT, August-October 2002 ..................................................... $12,242 84. “Iowa DOT Linear Referencing System: Preliminary Linear Data Creation,” Iowa DOT, May 2002-Dec 31, 2004 ........................................................ $239,102 83. “Incident Location Tool for Georgia,” Georgia DOT, 7/02-3/03 ................................................... $49,971 82. “Incident Location Tool for New York,” Technology Enterprise Group, 4/02-7/02 ...................... $42,076 81. Co-P.I. (25%), “Planning, Implementation and Operation of the IPMP, Phase 8,” Iowa DOT, June 2002-May 2003 .................................................................................. $201,094 80. “GIS-Based Incident Location Tool, Phase 8,” Iowa DOT, 7/02-7/03 ............................................ $57,361 79. Co-P.I. (50%), “Pedestrian Crossing Safety Tech. Assessment,” Iowa DOT, 6/02-12/02 ............................................................................................................................. $15,587 78. “Change Detection Analysis: Phase 2,” Iowa DOT, May 2002-May 2003 .................................... $17,500 77. “Advanced Technologies in Roadway Feature Collection for Design, Performance,

Emissions and Security Assessment: Phase 3,” U.S. DOT/University of California, Santa Barbara, including two outreach scans/visits to India, May 2002-May 2004 ............................... $107,596

76. “Iowa DOT Internet-Based Road Work Report, Year 3,” Iowa DOT, 4/02-12/02 .......................... $19,880 75. “GIS-ALAS TraCS Conversion Software,” GTSB, 10/01-9/02 ..................................................... $21,000 74. “ITSDS, Year 3,” GTSB, 10/01-9/02 .............................................................................................. $50,000 73. “GIS-Based Incident Location Tool, Phase 7” Iowa DOT, 7/01-6/02 ............................................ $63,968 72. Co-P.I. (50%), “Application of Advanced Remote Sensing Technology to Transportation Asset Management,” MTC and Iowa DOT, August 2001-February 2003 .................................... $226,455 71. “Causation and Mitigation of High Crash Locations: Enhancing the ITSDS (includes 4/3 lane conversion, paved shoulders and EB expressway,” Iowa DOT, 6/01-6/05 ..................... $145,190 70. Co-P.I. (50%), “Comparison of LIDAR and Photogrammetry for Highway Planning and Design,” Phase 2, Iowa DOT, May 2001-May 2002 ................................................................ $27,552 69. P.I. (50%), “Use of Remotely Sensed Data for Infrastructure Management: Phase 2,” U.S. DOT/University of California, Santa Barbara, May 2001-May 2002 .................... $94,750 68. Co-P.I. (25%), “Planning, Implementation and Operation of the Iowa Pavement Management Program: Phase 7,” Iowa DOT, May 2001-April 2002 .......................... $245,669 67. Co-P.I. (30%), “Identification of High Priority Corridors for Access Management,” Iowa DOT, April 2001-March 2002 ................................................................................................ $45,000 66. “Iowa DOT Internet-Based Road Work Report, Year 2” Iowa DOT, 3/01-12/01 ........................... $20,895 65. “GIS-Based Incident Location Tool, Phase 6: Implementation and Agency Support,” Iowa DOT, January-June 2001 ........................................................................... $45,000 64. “ITSDS, Year 2,” GTSB, October 2000-September 2001 .............................................................. $15,000 63. “Emergency Response Information System (ERIS): Phase 2” Iowa Department of Public Health, October 2000-September 2001 ........................................................................... $25,000

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62. “GIS-Based Incident Location Tool, Phase 5” Iowa DOT, 7/00-12/00 ........................................... $30,392 61. Faculty Associate, “Origin Destination Model Estimation for I-235 Traffic Simulation Study,” Sverdrup Corp., June 2000-June 2001 ............................................................. $10,000 60. “Paved Shoulder Analysis and Public Information,” Iowa DOT, 7/00-6/01 ................................... $15,000 59. “Remote Sensing to Support Linear Referencing Systems,” Iowa DOT, 7/00-6/01........................ $22,500 58. “GIS-Based Incident Location Tool, Phase 4,” Iowa DOT, January-June 2000 ............................ $45,876 57. “Iowa DOT Internet-Based Road Work Report, Year 1,” Iowa DOT, 3/00-12/00 ......................... $20,000 56. “Use of Remotely Sensed Data for Infrastructure Management, Access Management and Inventory,” U.S. DOT/UC Santa Barbara, May 2000-May 2001 ............................................ $72,250 55. Co-P.I. (25%), “Planning, Implementation and Operation of the IPMP: Phase 6,” Iowa DOT, February 2000-April 2001 .......................................................................................... $249,631 54. Co-P.I. (15%), “Implementation of the Iowa DOT PMOM,” Iowa DOT, 2/00-1/01 ................... $149,937 53. P.I. (90%), “Systematic Identification of High Crash Locations,” IHRB, 1/00-6/01 .................... $126,235 52. “Eisenhower Fellowship for Graduate Studies,” Student: Chris Monsere, Field Validation and Computer Automation of Statewide Freight Flow Model, U.S. DOT, 1/00-12/00 ................... $27,000 51. “Development of Internet Based RWIS (Roadway Weather Information System) AWOS (Airport Weather Observation System) Information Delivery Tools (AKA Weatherview),” Iowa DOT, October 1999-June 2005 .................................................................. $236,968 50. “ITSDS: Year 1,” GTSB, October 1999-September 2000 .............................................................. $15,000 49. “Eisenhower Fellowship for Graduate Studies,” Student: Richard Storm, GIS Based Calibration and Validation of Systems Planning Models, U.S. DOT, 8/99-8/01 ............................ $36,600 48. “Implementation of GIS at Iowa DOT, Phase 7: Construction Status Web Site, Linear

Referencing System Team Support and Technical Support of DOT GIS Team,” Iowa DOT, June-December 1999 .................................................................................................... $30,686 47. “GIS-Based Incident Location Tool, Phase 3” Iowa DOT, July-December 1999 ........................... $23,256 46. “GIS/Tranplan Revision Project,” Iowa DOT, Office of Systems Planning, 6/00-6/00 .................. $49,166 45. “GIS Accident Location and Analysis System (GIS-ALAS), Phase 3, Tasks: Access- ALAS Interface, ERIS (Emergency Response Information System) Location Tool and Safety System Analysis/Documentation,” Iowa DOT, 1/99-6/01 ............................................ $75,000 44. “Crash Outcomes Data Evaluation System (CODES),” Iowa Department of Health, October 1998-September 2000 ....................................................................................................... $33,500 43. “GIS-ALAS Phase 3” Iowa DOT, January 1999-June 2000 .......................................................... $109,991 42. “GIS-Based Incident Location Tool, Phase 2” Iowa DOT, January-June 1999 .............................. $39,995 41. “Development of Federal Data Workbooks and GIS Applications: Employment, Freight and Geospatial Data” U.S. DOT, Bureau of Transportation Statistics, 9/98-1/99 .......................... $60,000 40. Co-P.I. (50%), “Development and Training for a Crash Information System,” City of Cedar Falls Police Department, September-December 1998 ................................................ $3,941 39. “GIS-Based Incident Location Tool: Phase 1,” Iowa DOT, August-December 1998 .................... $24,908 38. “Maintenance Division Application Development and Training,” Iowa DOT, 2/98-12/98 ............ $23,130 37. “Implementation of GIS at Iowa DOT, Phase 6: Support GIS Coordinating Committee,

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Develop Linear Reference System RFP, Develop GIS Applications in Environmental, GPS and Rail, Develop Construction Status Web Site, Onsite GIS Software Support, Roadside Development Application, “Iowa DOT, February 1998 - May 1999 .............................. $99,995 36. “GIS-ALAS: Phase 2,” Iowa DOT, January-December 1998 ......................................................... $80,000 35. P.I., Coordination of Data Elements to support ISTEA Management Systems, Phase 2, Statewide Implementation,” Iowa DOT, July 1997-December 1998 ............................... $79,861 34. Co-P.I. (25%), “Planning, Implementation and Operation of the IPMP, Phase 5: Implementation and Operation of the IPMP,” Iowa DOT, January-December 1999 ................... $249,056 33. “Eisenhower Fellowship for Graduate Studies,” Student: Dave Preissig, Multi-modal, Multi-commodity Statewide Freight Model, U.S. DOT, June 1996 - May 1998 ........................... $48,610 32. “Improved Employment Data for Transportation Planning,” Iowa DOT, 1/97-6/98 ....................... $76,433 31. “GIS Traffic Planning Tools,” IHRB, May 1997-August 1998 ....................................................... $57,015 30. “Implementation of GIS at Iowa DOT, Phase 5: Support GIS Coordinating Committee, Location Reference Team Support, Revise/Update GIS Strategic Plan, Develop GIS Data, Training, Standards and Procedures, Communications and Marketing Strategy, Test GIS Software for Systems Compatibility,” Iowa DOT, 4/97-1/98........................................... $89,910 29. “GIS-ALAS: Phase 1,” Iowa DOT, January - December 1997 ....................................................... $75,798 28. “Statewide Transportation Planning Model and Methodology Development Program, Phase 2: Freight Commodity Models,” Iowa DOT, October 1996-December 1998 .................... $105,586 27. “GIS Technology Transfer of Transportation Modeling Environment to Local Agencies,” Priority Technology Program of the FHWA, U.S. DOT, August-December 1996 ......................... $10,083 26. “Eisenhower Fellowship for Graduate Studies,” Student: Michael D. Anderson, Integration of Travel Demand Models and GIS, U.S. DOT, August 1996 - May 1999 .................................... $72,000 25. P.I., Coordination of Data Elements to support ISTEA Management Systems: Phase 1,” Iowa DOT, March 1996-June 1997................................................................................ $119,992 24. “Implementation of GIS at Iowa DOT, Phase 4: Support GIS Coordinating Committee, Mapping and Conversion, GPS Applications, Orthophotography Assessment, Support Iowa Geographic Information Council and GIS Pilot Projects, including Sufficiency Data Access, Crash Node Mapping, Utility Inventory, Accidents and Roadside Features, Access

Locations, Project Level Data, Detour Locations, Mitigation Areas, Routing, Parcel Inventory, Pavement Management, Travel Demand Modeling, Socioeconomics and

Demographics and Statewide Freight Flow Models,” Iowa DOT, 1/96-3/97 ................................ $117,500 23. “Implementation of GIS at Iowa DOT, Phase 3: GIS Implementation Plan, Apps. Dev’l, Training, Selection and Orientation of GIS Coordinator,” Iowa DOT, 7/95-12/95......................... $18,988 22. Faculty Associate, “Early Deployment Study, Intelligent Transportation Systems for Des Moines, Iowa,” FHWA, U.S. DOT and Iowa DOT, 4/95-7/97 ................................................ $35,000 21. “Statewide Transportation Planning Model and Methodology Development Program, Phase 1,” Iowa DOT and MTC, January-December 1995 ............................................................ $101,556 20. “Implementation of GIS at Iowa DOT, Phase 2: GIS Impl. Plan, Apps Dev’l, Training, Database Development and Software Evaluation,” Iowa DOT, 1/95-6/95 ...................................... $39,561 19. “Development of Applications for Interactive Transportation Planning GIS,” MTC

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and Iowa DOT, December 1994 - June 1996 .................................................................................. $94,402 18. “Newsletter Publication and Administrative Support of Iowa Geographic Information Council,” Iowa Department of Economic Development/Iowa Rural Development Commission, December 1994 - December 1996 ............................................................................... $4,962 17. “Eisenhower Fellowship for Graduate Studies,” Student: Michael D. Anderson, U.S. DOT, September 1994-May 1996 ........................................................................................... $40,714 16. “Development of Computer Code and ITC GIS Lab Facility,” Iowa DOT, 1/94-12/94 ................... $8,769 15. “Implementation of GIS at Iowa DOT, Phase 1: GIS Strategic Plan and Institutional Structural Assessment” Iowa DOT, plus $39,725 in kind for equipment, 6/93-12/94 ................. $115,303 14. “High Speed Computing to Facilitate Real Time Analysis of Transportation Planning Alternatives through GIS,” MTC and Iowa DOT, July 1993-September 1994 ............................... $65,920 13. “A GIS-Based Travel Demand Modeling System for Supercomputing,” Cray Research, Inc., January-December 1993 ......................................................................................... $18,500 12. “Needs Assessment: Traffic Data Storage, Processing and Dissemination,” Nevada DOT, January-December 1992 ........................................................................................... $25,000 11. “GIS Planning and Resource Mapping for the Lake Mead National Recreation Area,” U.S. National Park Service, January-December 1992 ..................................................................... $83,297 10. “Development of a Census Geography to Traffic Analysis Zone Correspondence Table,” Regional Transportation Commission of Clark County, Nevada, 1/92-12/92 .................... $10,000 9. Co-P.I. (50%) (with S. Sathisan), “Functional Requirements Study for a Geographical

Information System at the Nevada DOT,” Nevada DOT, January-December 1992 ....................... $24,000 8. P.I., Cooperative Agreement between the Nevada DOT, Southern Nevada Planning Division and the UNLV Transportation Research Center, “Southern Nevada Transportation Planning and Modeling,” May-August 1992 .......................................................... $38,200 7. “GIS for Colorado River Transportation Study Automation,” City of Bullhead City, AZ, January-December 1992 ........................................................................................................... $31,721 6. “Development of a Computerized System for Travel Demand Management – Rideshare

Matching,” Clark County Regional Transportation Commission, 1/92-12/92 ............................... $20,000 5. “GIS-Based Assessment of Impacts of Rail Access to Yucca Mountain,” Nevada Agency for Nuclear Projects, Carson City, NV, January-December 1992 ..................................... $55,009 4. “Application of RADTRAN to Nevada Transportation Routes,” Nevada Agency for Nuclear Projects, Carson City, NV, January-December 1992 ........................................................ $13,712 3. P.I., Cooperative Agreement between the Nevada DOT, Southern Nevada Planning Division and the UNLV Transportation Research Center, “Southern Nevada Transportation Planning and Modeling,” May-August 1991 .......................................................... $23,400 2. Co-P.I. (33%) (with S. Sathisan and R. di Bartolo), “Yucca Mountain Transportation Routes: Preliminary Characterization and Risk Analysis,” Nevada Agency for Nuclear Projects, August 1989-December 1991 ............................................................................ $450,000 1. “Trip Generation Analysis,” Regional Transportation Commission of Southern Nevada, August 1990-May 1991 ..................................................................................................... $45,000

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Self Funded Research

• Roundabout perception and safety (with C. Harding in Human Computer Interaction (HCI) and A. Pratelli, Univ. of Pisa), 2009-2010

• Haptics and Transportation Planning and Design, 2008-2010 (with C. Harding in HCI) • Remote Sensing Applications in Transportation, 1999. • A Forensic Analysis of Iowa Urban Travel Demand Model Performance, 1997/1998. • Investigations of Byproduct Radiations and Ultrasonic Measurements for Various Transportation

Applications (with W. Anderson), 1996-1997. • Linking Travel Demand and Highway Capacity Models, 1993-1994. • Highway VMT Growth as a Self-Limiting Process: Implications for the Future of Congestion, 1989-

1995. • Technological Innovation and the Relations between Transportation and Production, 1989-1995.

REFEREED JOURNAL PUBLICATIONS

REFEREED JOURNAL PUBLICATIONS IN PROGRESS (Note: Student co-authors indicated by asterisk * )

3. Li, Wen*, M. Pawlovich, A. Carriquiry, and R. Souleyrette, “A hierarchical Poisson-Gamma-Normal model to explore associations between bypass type and safety.” To be submitted to Transportation Research, Part B – Methodological.

2. Rentziou, K.*, K. Gkritza and R. Souleyrette, “VMT, energy consumption, and greenhouse gas emissions forecasting for passenger transportation.” To be submitted to Transportation Research, Part A- Policy and Practice.

1. Hallmark, S., L. Boyle, T. Maze, A. Carriquiry, N. Hawkins, O. Smadi, R. Souleyrette and T. McDonald. Developing road departure crash surrogates. ASCE Journal of Transportation Engineering, special issue, invited.

REFEREED JOURNAL PUBLICATIONS UNDER REVIEW

(Note: Student co-authors indicated by asterisk * )

4. Fitzsimmons, E.*, S. Nambisan and R. Souleyrette, “A comparison of techniques to collect vehicle operational data and develop trajectories and speed profiles through horizontal curves.” Submitted for publication in Transportation Research Record (TRR), Journal of the Transportation Research Board.

3. Cook, D.*, R. Souleyrette, and J. Jackson*, “Effect of Road Segmentation on Highway Safety Analysis.” Submitted for publication in Transportation Research Record (TRR), Journal of the Transportation Research Board.

2. Brown, J., K. Rentziou, S. Nambisan, and R. Souleyrette, “An Examination of Key Aspects for Railroad Electrification.” Submitted for publication in Transportation Research Record (TRR), Journal of the Transportation Research Board.

1. Baird, M.*, J. K. Gkritza, R. Souleyrette, and B. Danielson, “An Empirical Bayes Model to Assess Deer-Vehicle Crash Safety in Urban Areas in Iowa.” Submitted for publication in Transportation Research Record (TRR), Journal of the Transportation Research Board.

REFEREED JOURNAL PUBLICATIONS PENDING (Note: Student co-authors indicated by asterisk * )

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 12

35. Boeckenstedt, R., K. Gkritza, R. Souleyrette, and S. Nambisan, “Interdependencies between the Bioeconomy and the Transportation Infrastructure in Iowa.” Accepted for publication in Transportation Research Record (TRR), Journal of the Transportation Research Board.

34. Hochstein, J.*, T. Maze, R. Souleyrette, and T. Stout, “Rural Expressway Intersection Design Guidance: Suggestions for the AASHTO Green Book and MUTCD.” Accepted for publication in TRR Journal.

33. Sax, C.*, T. Maze, R. Souleyrette, N. Hawkins and A. Carriquiry, “Optimum urban clear-zone distance.” Accepted for publication in TRR Journal.

32. Harwood, D., K. Bauer, D. Gilmore, R. Souleyrette, and Z. Hans, “Validation of the usRAP Star Rating Protocol for Application to Safety Management of U.S. Roads.” Accepted for publication in TRR Journal.

REFEREED JOURNAL PUBLICATIONS PUBLISHED

(Note: Student co-authors indicated by asterisk * )

30. Harding, C. and R. Souleyrette, “Investigating the use of 3D graphics, haptics (touch) and sound for highway location planning.” Journal of Computer-Aided Civil and Infrastructure Engineering. 24 (2009) pp. 1–19.

29. Smadi, O., R. Souleyrette, D. Ormand* and N. Hawkins, “Pavement Marking Retroreflectivity: Analysis of Safety Effectiveness.” Transportation Research Record (TRR), Journal of the Transportation Research Board, No. 2056, 2008, pp. 17-24.

28. Hallmark, S., S. Lamptey* and R. Souleyrette, “Use of n-Fold Cross-Validation to Evaluate Three Methods to Calculate Heavy Truck Annual Average Daily Traffic and Vehicle Miles Traveled.” Journal of the Air and Waste Management Association. 57:4–13, January, 2007.

27. Souleyrette, R., R. Tenges*, T. McDonald, T. Maze and A. Carriquiry, “Safety Effectiveness of Stop Control at Ultralow-Volume Unpaved Intersections,” TRR No. 1967, 2006, pp. 58-65.

26. Stout, T.*, M. Pawlovich, R. Souleyrette and A. Carriquiry, “Safety Impacts of ‘Road Diets’ in Iowa.” ITE Journal. vol. 76, no. 12, December, 2006.

25. Veneziano, D.*, S. Hallmark and R. Souleyrette, “Accuracy of Light Detection and Ranging Derived Terrain Data for Highway Location,” Journal of Computer-Aided Civil and Infrastructure Engineering, Vol. 19, 2004, pp. 130-143.

24. Khattak, A., S. Hallmark and R. Souleyrette, “Application of Light Detection and Ranging (LIDAR) Technology to Highway Safety,” TRR No. 1836, 2003, pp. 7-15.

23. Hallmark, S., W. Schuman, S. Kadolph and R. Souleyrette, “Integration of Spatial Point Features with Linear Referencing Methods,” TRR, No. 1836, 2003, pp. 102-110.

22. Veneziano, D.*, R. Souleyrette and S. Hallmark, “Integration of Light Detection and Ranging (LIDAR) Technology with Photogrammetry in Highway Location and Design,” TRR, Journal of the Transportation Research Board, No. 1836, 2003, pp. 1-6.

21. Anderson, M.* and R. Souleyrette, “Pseudo-Dynamic Travel Model Application to Assess Traveler Information,” Transportation, Vol. 29, No. 3, August 2002, pp. 307-319.

20. Khattak, A., M. Pawlovich*, R. Souleyrette and S. Hallmark, “Factors Related to More Severe Older Driver Traffic Crash Injuries,” Journal of Transportation Engineering, Vol. 128, No. 3, May/June 2002, pp. 243-249.

19. Easa, S., T. Strauss, Y. Hassan and R. Souleyrette, “Three-Dimensional Transportation Analysis: Planning and Design,” Journal of Transportation Engineering, ASCE, Vol. 128, No. 3, May/June 2002, pp. 250-258.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 13

18. Shadewald, J.*, S. Hallmark and R. Souleyrette, “Visualizing System-Wide Economic Impacts of Transportation Projects,” Journal of Urban Planning and Development, Vol. 127, No. 4, December 2001, pp. 158-168.

17. Souleyrette, R., D. Plazak, T. Strauss and S. Andrle, “Applications of State Employment Data to Transportation Planning,” TRR, No. 1768, 2001, pp. 26-35.

16. Souleyrette, R., T. Maze, T. Strauss, D. Preissig* and A. Smadi, “Freight Planning Typology,” TRR, Journal of the Transportation Research Board, No. 1613, 1998, pp. 12-19.

15. Shanmuganathan, R.*, R. Souleyrette and T. Maze, “A Dynamic Bayesian Approach to Estimate the Impact of Speed Limit Changes,” TRR, No. 1640, 1998, pp. 47-56.

14. Souleyrette, R. and M. Anderson*, “Developing Small Area Network Planning Models using Desktop GIS,” Journal of Urban Planning and Development, Vol. 124, No. 2, June 1998, pp. 55-71.

13. Cadwallader, W. and R. Souleyrette, “GIS Aids in Romania’s Communism-to-Capitalism Transition,” GeoInfo Systems, Vol. 8, No. 1, January 1998, pp. 30-34.

12. Kamyab, A.*, T. Maze and R. Souleyrette, “Application of Vehicle Specific Information in Adaptive Intersection Traffic Signal Control,” Transportation Quarterly, Vol. 50, No. 2, Spring 1996, pp. 159-168.

11. Kamyab, A.*, T. Maze and R. Souleyrette, “Evaluation of Vehicle Specific Information in a Traffic Signal Control,” Journal of Transportation Engineering, Vol. 122, No. 6, November/December 1996, pp. 421-429.

10. Anderson, M.* and R. Souleyrette, “A GIS-Based Transportation Forecast Model for Use in Smaller Urban and Rural Areas,” TRR, No. 1551, 1996, pp. 95-104.

9. Pawlovich, M.*, E. Jaselskis and R. Souleyrette, “Emerging Concepts in Innovative Sign Management Programs,” TRR, No. 1553, 1996. pp. 12-17.

8. Garrison, W. and R. Souleyrette, “Transportation, Innovation and Development: The Companion Innovation Hypothesis,” The Logistics and Transportation Review, Vol. 32, No. 1, March 1996, pp. 1-20.

7. Souleyrette, R., Z. Hans*, W. Garrison and L. Wazny, “Analysis of Trends Underlying Urban/Regional Impacts of Traffic Growth,” Journal of Urban Planning and Development, Vol. 121, No. 4, December 1995, pp. 158-171.

6. Hans, Z.* and R. Souleyrette, “GIS and Network Models: Issues for Three Potential Applications,” Journal of Advanced Transportation, Vol. 29, No. 3, Fall 1995, pp. 355-373.

5. Souleyrette, R. and S. Sathisan, “Applications of GIS for Radioactive Materials Transportation,” Microcomputers in Civil Engineering (now Computer-Aided Civil and Infrastructure Engineering), Vol. 9, 1994, pp. 295-303.

4. Garrison, W. and R. Souleyrette, “The Relationship between Transportation and Innovation,” Transportation Quarterly, Vol. 48, No. 3, Summer 1994, pp. 257-265.

3. Robuste, F., C. Daganzo and R. Souleyrette, “Implementing Vehicle Routing Models,” Transportation Research Part B, Vol. 24B, No. 4, August 1990, pp. 263-286.

2. Garrison, W. and R. Souleyrette, “The Relations between Transportation and Production,” TRR, Journal of the Transportation Research Board, No. 1262, 1990, pp. 21-30.

1. Souleyrette, R., H. Mahmassani and C.M. Walton, “An Operational Typology for Toll Financing of Highway Facilities,” TRR, No. 1077, 1986, pp. 5-12.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 14

BOOK CHAPTER – PEER REVIEWED

1. Souleyrette, R. and T. Strauss (1999), “Transportation,” Urban Planning and Development Apps. of GIS, Said Easa and Yupo Chan (eds.), ASCE, Reston, VA, Chapter 7, pp.117-133

REFEREED CONFERENCE PAPERS (FULL PAPER, 3+REVIEWS) (Note: Student co-authors indicated by asterisk * )

22. Pratelli, A., R. Souleyrette and C. Harding, “Roundabout Perception: Review of Standards and Guidelines for Advanced Warning,” Sixteenth International Conference on Urban Transport and the Environment, Cyprus, May 2010.

22. Kim, B.*, R. Souleyrette and T. Maze, “Exclusive Median Bus Lanes: The Seoul Experience - with Suggestions and Comments on Extensibility,” Proceedings of the 87th Annual Meeting of TRB, Washington, DC, Jan. 2010.

21. Pratelli, A. and R. Souleyrette, “Visibility, Perception and Roundabout Safety,” Fifteenth International Conference on Urban Transport and the Environment, Bologna, June 2009, Built Environment volume 107. Pp. 577-588.

20. Souleyrette, R. “Highway Safety and iRAP: The Challenge of Heterogeneous Traffic Mixes,” International Conference on Best Practices to Relieve Congestion on Mixed-Traffic Urban Streets in Developing Countries, IIT Madras, Chennai, India. Sep. 12-14, 2008. Pp. 339-348.

19. Hallmark, S., L. Boyle, T. Maze, A. Carriquiry, N. Hawkins, O. Smadi, R. Souleyrette and T. McDonald. “Developing road departure crash surrogate events.” 10th International Conference on Application of Advanced Technologies in Transportation. Athens, May 2008.

18. Souleyrette, R., R. Haas and T. Maze, “Validation and Implication of Segmentation on Empirical Bayes for Highway Safety Studies,” Transactions of the Fourth International Conference on the Impact of Environmental Factors on Health, Malta, June 2007, pp. 85-94.

17. Souleyrette, R., T. McDonald and M. O’Brien, “Safety Effectiveness of All-Red Clearance Intervals at Urban Low-Speed Intersections,” Proceedings of the 86th Annual Meeting of TRB, Washington, DC, Jan. 2007.

16. Souleyrette, R. and D. Plazak, “Use of Geospatial Information and Remote Sensing Data to Support Improved Roadway Access Management,” Twelfth International Conference on Urban Transport and the Environment, Prague, July 2006, pp. 477-490.

15. Agarwal, M*, T. Maze and R. Souleyrette, “The Weather and Urban Freeway Traffic Operations,” Proceedings of the 85th Annual Meeting of TRB, Washington, DC, January 2006.

14. Harrison, S., S. Hallmark and R. Souleyrette, “Sensitivity Analysis of Travel Demand Models for Small and Medium-Sized Communities and Rural Areas,” 83rd Annual Meeting of TRB, Washington, DC, January 2004.

13. Plazak, D. and R. Souleyrette, “Process to Identify High Priority Corridors for Access Management Near Large Urban Areas in Iowa Using Spatial Data,” Proceedings of the TRB Annual Access Management Conference, Austin, TX, June 2002.

12. Veneziano, D.*, S. Hallmark, K. Mantravadi* and R. Souleyrette, “Evaluating Remotely Sensed Images for Use in Inventorying Roadway Features,” 7th International Conference on Application of Advanced Technologies in Transportation, Cambridge, MA, August 2002.

11. Souleyrette, R., A. Kamyab, Z. Hans and A. Khattak, “Systematic Identification of High Crash Locations,” Proceedings of the 81st Annual Meeting of TRB, Washington, DC, January 2002.

10. Anderson, M.* and R. Souleyrette, “A Network Demand Model for Rural Bypass Planning,” Proceedings of the 79th Annual Meeting of TRB, Washington, DC, January 2000.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 15

9. Khattak, A., M. Pawlovich* and R. Souleyrette, “An Investigation of Injury Severity of Older Drivers in Iowa,” 79th Annual Meeting of TRB, Washington, D. C., January, 2000.

8. Strauss, T., R. Souleyrette, D. Gieseman and T. Maze, “Development of a GIS-Based Crash Location Tool,” 6th World Congress on Intelligent Transportation Systems, Toronto, Oct. 1999.

7. Anderson, M.*, W. Vodrazka* and R. Souleyrette, “Iowa Travel Model Performance, 20 Years Later,” Transportation, Land Use and Air Quality, ASCE, Portland, May 1998, pp. 586-595.

6. Albrecht, C.*, D. Plazak and R. Souleyrette, “Access Management and Land Use: A Proposed Process,” Transportation, Land Use and Air Quality, ASCE, Portland, May 1998, pp. 94-103.

5. Sathisan, S., R. Souleyrette and S. Lim*, “GIS-Based Applications for Rail Infrastructure Analysis,” Guessing the Future: Coping with Uncertainty in Infrastructure Planning and Infrastructure Management, ASCE, Denver, July 21-23, 1993, pp. 347-351.

4. Souleyrette, R., S. Sathisan and E. Parentela*, “Hotel-Casino Trip Generation Analysis Using GIS,” Site Traffic Impact Assessment, ASCE, Chicago, June 8-10, 1992, pp. 52-56.

3. Souleyrette, R., S. Sathisan, D. James and S. Lim*, “GIS for Transportation and Air Quality Analysis,” Transportation Planning and Air Quality, ASCE, New York, 1991, pp. 182-194.

2. Halstead, R., R. Souleyrette and R. di Bartolo, “Transportation Access to Yucca Mountain: Critical Issues,” Public Safety and Technical Achievement, ASCE, 1991, pp. 647-656.

1. Walton, C.M., M. Euritt and R. Souleyrette, “Private Participation in Financing Highway Projects and Providing Property for Highway Improvements,” Understanding the Highway Finance Evolution/Revolution, AASHTO, Washington, DC, 1987.

OTHER SIGNIFICANT PEER REVIEWED PUBLICATIONS

3. Co-editor, “Improving National Transportation Geospatial Information,” Transportation Research Board, Committee on Geographic Information Science and Applications ABJ60 (White Paper report on a conference held in December, 2007, Washington, D.C.). June, 2009. Available at www.ABJ60.net.

2. Co-author, “Integrating Roadway, Traffic and Crash Data,” Transportation Research Circular E-C111, National Academy of Sciences, Transportation Research Board, online, available at http://onlinepubs.trb.org/onlinepubs/circulars/ec111.pdf, January, 2007.

1. Contributor, “Geospatial Information Technologies for Asset Management,” Transportation Research Circular E-C108, National Academy of Sciences, Transportation Research Board, online, available at http://onlinepubs.trb.org/onlinepubs/circulars/ec108.pdf, October, 2006.

REFEREED CONFERENCE PAPERS (FULL PAPER, ABSTACT REVIEW ONLY) (Note: Student co-authors indicated by asterisk * )

39. Maze, T., Smith, T., C. Albrecht, M. Orellana*, A. Carriquiry and R. Souleyrette, “Estimating the Relationship between Snow and Ice Maintenance Performance and Current Weather Conditions,” 16th World Congress and Exhibition on Intelligent Transport Systems and Services, Stockholm, Sweden, September, 2009.

38. Hallmark, S., L. Boyle, T. Maze, A. Carriquiry, N. Hawkins, O. Smadi, R. Souleyrette and T. McDonald, “Developing Road Departure Crash Surrogates,” 10th International Conference on Application of Advanced Technologies in Transportation, Athens, Greece, May 27-31, 2008 .

37. Chai, X.*, N. Hawkins and R. Souleyrette, “A Hybrid Approach for Determining Traffic Demand in Large Development Areas,” Mid-Continent Trans Research Symposium, Ames, Aug 2007.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 16

36. Souleyrette, R., T. McDonald and D. Kroeger, “Assessment of Channelizing Device Effectiveness on High Speed/High Volume Roadways,” Mid-Continent Transportation Research Symposium, Ames, August 16-17, 2007.

35. Lund, V.*, R. Souleyrette and T. Stout, “70-MPH Speed Limit: Speed Adaptation, Spillover and Surrogate Measures of Safety,” Mid-Continent Trans Research Symposium, Ames, Aug 2007.

34. Stout, T. and R. Souleyrette, “The Impact of Some Site-Specific Characteristics on the Success of the Signalization of High-Speed Intersections,” Research Pays Off - Mid-Continent Transportation Research Symposium, Madison, Wisconsin, August 17-18, 2006.

33. Stout, T.* and R. Souleyrette, “Analyzing Crash Risk Using Automatic Traffic Recorder Speed Data,” Mid-Continent Transportation Research Symposium, Ames, August 18-19, 2005.

32. Agarwal, M.*, T. Maze and R. Souleyrette, “Impacts of Weather on Urban Freeway Traffic Flow Characteristics and Facility Capacity,” Mid-Continent Transportation Research Symposium, Ames, August 18-19, 2005.

31. Knox, T.* and R. Souleyrette, “Safety Assessment of Installing Traffic Signals at High-Speed Expressway Intersections,” Mid-Continent Transportation Research Symposium, Ames, August 18-19, 2005.

30. Tenges, R.* and R. Souleyrette, “Guidelines for the Removal of Traffic Control Devices in Rural Areas,” Mid-Continent Transportation Research Symposium, Ames, August 18-19, 2005.

29. Plazak, D. and R. Souleyrette, “Process to Identify High Priority Corridors for Access Management Near Large Urban Areas in Iowa Using Spatial Data,” Mid-Continent Transportation Research Symposium, Ames, August 21-22, 2003.

28. Hans, Z., R. Tenges*, S. Hallmark, R. Souleyrette and S. Pattnaik*, “Use of LiDAR-Based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment,” Mid-Continent Transportation Research Symposium, Ames, August 21-22, 2003.

27. Pattnaik, S.*, S. Hallmark and R. Souleyrette, “Collecting Road Inventory using LIDAR Surface Models” Map India, Delhi, January 31, 2003.

26. Souleyrette, R. and S. Pattnaik*, “Designing a Traffic Monitoring Program using Landuse Change Detection,” Map India, Delhi, January 31, 2003.

25. Veneziano, D.*, Souleyrette, R. and S. Hallmark, “Evaluation of LIDAR for Highway Planning, Location and Design,” Pecora 15/Land Satellite Information IV, November 2002, Denver, CO.

24. Khattak, A., M. Pawlovich and R. Souleyrette, “Crash Injury Severity of Older Drivers in Iowa,” Proceedings of the Mid-Continent Transportation Symposium, Ames, Iowa, May 15-16, 2000, pp. 235-240.

23. Preissig, D.* and R. Souleyrette, “Multimodal Statewide Freight Transportation Modeling Process,” Metropolitan Conference on Public Transportation Research, University of Illinois at Chicago, June 11, 1999, pp. 147-156.

22. Souleyrette, R. and D. Gieseman, “Development of an Automated Crash Location System for Iowa,” Geographic Information Systems for Transportation Symposium, AASHTO, San Diego, CA, April, 1999 (http://www.bts.gov/programs/gis/BTSWEB/GIS-T_99/Session_23/232.html).

21. Anderson, M.* and R. Souleyrette, “Quick-Response Bypass Forecasting for Small Urban Communities using an Economic Gravity Model for External Trip Analysis,” Crossroads 2000, Ames, IA, August 19-20, 1998, pp. 67-70.

20. Anderson, M.* and R. Souleyrette, “Simulating Traffic for Incident Management and ITS Investment Decisions,” Crossroads 2000, Ames, IA, August 19-20, 1998, pp. 7-11.

19. Pawlovich, M.*, R. Souleyrette and T. Strauss, “A Methodology for Studying Crash Dependence on Demographic and Socioeconomic Data,” Crossroads 2000, Ames, IA, August 19-20, 1998, pp. 209-215.

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18. Schuman, W., T. Strauss, D. Gieseman* and R. Souleyrette, “Iowa DOT Statewide Coordinated GIS,” Crossroads 2000, Ames, IA, August 19-20, 1998, pp. 187-191.

17. Cao, C.*, T. Strauss, R. Souleyrette and D. Shinn, “Transportation and Urban Form: A Case Study - Des Moines Metropolitan Area,” Crossroads 2000, Ames, IA, Aug 1998, pp. 232-237.

16. Estochen, B.*, T. Strauss and R. Souleyrette, “An Assessment of Emergency Vehicle Response Pre-Deployment Using GIS Identification of High-Accident Density Locations,” Crossroads 2000, Ames, IA, August 19-20, 1998, pp. 221-226.

15. Souleyrette, R., T. Strauss, M. Pawlovich and B. Estochen, “Safety Data in a GIS Environment: New Tools for the Four Es,” 24th Annual International Forum on Traffic Records and Highway Information Systems, Minneapolis, MN, July 26-29, 1998.

14. Souleyrette, R., T. Strauss, M. Pawlovich and B. Estochen, “GIS ALAS, The Integration and Analysis of Highway Crash Data in a GIS Environment,” Geographic Information Systems for Transportation Symposium, AASHTO, Salt Lake City, Utah, April 20-22, 1998, pp. 411-428.

13. Hans, Z., O. Smadi, T. Maze, R. Souleyrette and J. Resler,*, “Iowa’s Pavement Management Program Database: Issues and Design Considerations,” Maintenance Management, AASHTO/TRB, Saratoga Springs, New York, July 1997.

12. Pawlovich, M.* and R. Souleyrette, “A GIS-based Accident Location and Analysis System,” TRB Semi sesquicentennial Transportation Conference, Ames, Iowa, May 1996, pp. 29-34.

11. Mescher, P.* and R. Souleyrette, “GIS to Facilitate the Bicycle Facility Planning Process,” AASHTO GIS-T Symposium, Kansas City, April 1996, pp. 283-306.

10. Souleyrette, R., “Issues in Implementing GIS and GPS,” Professional Surveyor, Vol. 15, No.7, October 1995, pp. 24-30.

9. Maze, T., A. Smadi and R. Souleyrette, “An Iowa Approach to Statewide Freight Demand Models or the Onion Approach to Freight Demand Forecasting,” Urban Goods and Freight Forecasting Conference, Albuquerque, Sep 1995, pp.13.1-13.8.

8. Souleyrette, R., J. Whitaker and Sh. Sathisan, “Options for Implementation of GIS at the Nevada DOT,” AASHTO GIS-T Symposium, Albuquerque, NM, 1993, pp. 291-301.

7. Souleyrette, R., W. Vodrazka and F. Dilger, “Using GIS to Support Regional Transportation Modeling,” 9th Intl. Conference on Systems Engineering, Las Vegas, 1993, pp. 146-150.

6. Parentela, E., R. Souleyrette and D. Croce*, “GIS as a Traffic Monitoring System Tool,” 46th ITE District 6 Meeting Compendium of Technical Papers, Las Vegas, NV, 1993, pp. 111-118.

5. Dilger, F., P. Lima and R. Souleyrette, “A Geographical Information/Transportation Modeling System,” 46th ITE District 6 Meeting Compendium, Las Vegas, NV, 1993, pp. 85-90.

4. Sathisan, S., E. Parentela, R. Souleyrette and E. Neumann, “Knowledge-Based Expert System to Monitor Impacts of Transporting Radioactive Materials,” Intl. Conf. on Artificial Intelligence Applications in Transportation Engineering, San Buenaventura, June 1992, pp. 479-492.

3. Parentela, E.*, S. Sathisan and R. Souleyrette, “A Study of the Effectiveness of Bus Turnouts,” 43rd ITE District 6 Meeting, Boise, ID, 1990, pp. 237-246.

2. Garrison, W. and R. Souleyrette, “Transportation, Innovation and the Space Economy,” 1989 Meeting of the Regional Sciences Association, Santa Barbara, CA, October 1989.

1. Walton, C.M., R. Souleyrette and H. Mahmassani, “Tolling Concepts in Highway Financing,” Symposium on Innovative Financing for Transportation: Sharing Solutions to Shared Problems, University of Virginia, December 11-13, 1985.

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TECHNICAL REPORTS, SOFTWARE AND ARCHIVAL DATASETS

90. w/Z. Hans. Curve Location and Parameter GIS Database, Iowa DOT, September, 2009. 89. Maze, T.H., J. Hochstein,* R. Souleyrette, H. Preston and R. Storm, Report 650: Median Intersection

Design for Rural High-Speed Divided Highways, Transportation Research Board, National Cooperative Highway Research Program (NCHRP), Project 15-30. May, 2010. 167 pp.

89. Preston, H., T. H. Maze, W. Stein and R. Souleyrette, Research Results Digest 345, Alternative Strategies for Safety Improvement Investments, NCHRP Project 17-18(19). April, 2010. 28 pp.

88. Souleyrette, R., T. Stout and A. Carriquiry. Evaluation of Iowa’s 70 mph Speed Limit – 2.5 Year Update, Iowa DOT, CTRE Project 06-247, January 2009. 45 pp.

87. Stout, Thomas B. and R., Impact of Some Site-Specific Characteristics on the Success of the Signalization of High-Speed Intersections, Iowa DOT, CTRE Proj 05-236, June 2008. 28 pp.

86. Harwood, Doug, R. Souleyrette, David K Gilmore, Darren J. Torbic and Z. Hans, usRAP Pilot Program Phase 2, AAA Foundation for Traffic Safety, January 2008. 88 pp.

85. Gieseman, D., N. Burdine and R. Souleyrette, Crash Mapping and Analysis Tool for Minnesota DOT (MNMAT), Map Objects and Visual Basic, 2007.

84. Souleyrette, R. and N. Burdine, State Highway Safety Engineers List Serve and Archive, web site: http://statehighwaysafetyengineers.org, FHWA, July, 2007 - present.

83. Souleyrette, R., T. McDonald and Dennis Kroeger, Assessment of Channelizing Device Effectiveness on High Speed/High Volume Roadways. Iowa DOT, CTRE Project 06-278, July 2007. 66 pp.

82. Hawkins, N., R. Souleyrette, X. Chai* and P. Hanley, Development of a New Process for Determining Design Year Traffic. Iowa DOT, IHRB Project TR-528, April 2007. 55 pp.

81. Souleyrette, R. and T. Stout, Crash Data Validation: An Iowa Case Study. Iowa DOT, CTRE Project 06-256, February 2007. 27 pp.

80. Harwood, D., R. Souleyrette, D. Torbic and Z. Hans, United States Road Assessment Program Feasibility Assessment/Pilot Program. AAA Foundation for Traffic Safety May 2006. 117 pp.

79. Gieseman, D., N. Burdine and R. Souleyrette, Incident Mapping and Analysis Tool for New York, Map Objects and Visual Basic, 2005.

78. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for North Dakota, Map Objects and Visual Basic, 2005.

77. R. Souleyrette, R. Tenges*, T. McDonald and T. Maze, Guidelines for Removal of Traffic Control Devices in Rural Areas, Iowa Highway Res. Board, Project TR-527, Oct 2005. 80 pp.

76. R. Souleyrette and T. Knox*, Safety Effectiveness of High-Speed Expressway Signals, Aug 2005. 23 pp. 75. M. Agarwal*, T. Maze and R. Souleyrette, Impact of Weather on Urban Freeway Traffic Flow

Characteristics and Facility Capacity, August 2005. 74. Souleyrette, R., S. Hallmark, M. DeLong* and Z. Hans, Remote Sensing Change Analysis Methodology

to Support Traffic Monitoring Programs: Phase 2I, Iowa DOT and National Consortium for Remote Sensing in Transportation, UC Santa Barbara. CTRE Report #03-147, June 2004. 21 pp.

73.Souleyrette, R., M. O’Brien*, T. McDonald, H. Preston and R. Storm, Effectiveness of All-Red Clearance Interval on Intersection Crashes, Minnesota DOT Local Roads Research Board, Report #MN/RC-2004-26, May 2004. 166 pp.

72. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for South Dakota, Map Objects and Visual Basic, 2004.

71. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for Florida, Map Objects and Visual Basic, 2004.

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70. Gieseman, D., N. Burdine and R. Souleyrette, Incident Mapping and Analysis Tool (IMAT) for TraCS (Traffic and Criminal Software), Map Objects and Visual Basic, 2004.

69. Gieseman, D., N. Burdine and R. Souleyrette, Crash Mapping and Analysis Tool (CMAT), Map Objects and Visual Basic, 2004.

68.Souleyrette, R., S. Hallmark, S. Pattnaik*, M. O’Brien* and D. Veneziano*, Grade and Cross Slope Estimation from LIDAR-based Surface Models, CTRE Report MTC Project 2001-02, ISU, October 2003. 28 pp.

67. Hans, Z., S. Hallmark, R. Souleyrette, R. Tenges and D. Veneziano*, Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, MTC Project 2001-02, ISU, October 2003. 50 pp.

66.Souleyrette, R., S. Hallmark, M. O’Brien*, S. Pattnaik* and Z. Hans, Remote Sensing Change Analysis Methodology to Support Traffic Monitoring Programs, CTRE, ISU, July 2003.

65. Kannel, E., R. Souleyrette and R. Tenges*, In-Street Yield to Pedestrian Sign Application in Cedar Rapids, Iowa, CTRE, ISU, May 2003.

64. Souleyrette, R., T. McDonald and R. Tenges*, Angle Parking on Iowa’s Low Volume Primary Extensions in Small Towns, CTRE, ISU, January 2003.

63. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for Delaware, Map Objects and Visual Basic, 2003.

62. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for Georgia, Map Objects and Visual Basic, 2003.

61. Gieseman, D., N. Burdine and R. Souleyrette, Incident Location Tool for New York, Map Objects and Visual Basic, 2002.

60. Plazak, D. and R. Souleyrette, Process to Identify High-Priority Corridors For Access Management Near Large Urban Areas in Iowa, CTRE, ISU, December 2002.

59. Souleyrette, R., Z. Hans, N. Burdine and J. Roche*, Emergency Response Information System CD and Documentation, CTRE, ISU, July 2002.

58. Veneziano, D., S. Hallmark and R. Souleyrette, Comparison of LIDAR & Conventional Mapping Methods for Highway Corridor Studies, CTRE, ISU, June 2002.

57. Gieseman, D. and R. Souleyrette, Incident Location Software User’s Manual, CTRE, ISU, December 2001.

56. Souleyrette, R., T. McDonald, Z. Hans, A. Kamyab and T. Welch, Paved Shoulders on Primary Highways in Iowa: An Analysis of Shoulder Surfacing Criteria, Costs and Benefits, CTRE, ISU, November 2001.

55. Hallmark, S., K. Mantravadi*, R. Souleyrette and D. Veneziano*, Use of Remote Sensing for Collection of Data Elements for Linear Referencing Systems, CTRE, ISU, September 2001.

54. Souleyrette, R., S. Veeramallu* and S. Hallmark, Use of Remote Sensing to Identify Access Elements for Safety Analysis, CTRE, ISU May 2001.

53. Hallmark, S., K. Mantravadi*, D. Veneziano* and R. Souleyrette, Evaluating Remotely Sensed Images for use in Inventorying Roadway Infrastructure Features, CTRE, ISU, May 2001.

52. Souleyrette, R., A. Kamyab, Z. Hans, K. Knapp and A. Khattak, Systematic Identification of High Crash Locations, CTRE, May 2001.

51. Storm, R.*, J. Shadewald,* and R. Souleyrette, GIS/Tranplan Enhancement Software and Documentation, CTRE, ISU, December 1999.

50. Monsere, C.*, R. Souleyrette and C. Cao*, CD ROM and Workbooks for Federal Data Users: Freight, Employment and Spatial Data, CTRE, ISU, August 1999.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 20

49. Estochen, B.* and R. Souleyrette, Crash Outcomes Data Evaluation System (CODES) GIS Development, CTRE, ISU, May 1999.

48. Souleyrette, R., T. Strauss, M. Pawlovich* and B. Estochen*, GIS-Based Accident Location and Analysis System (GIS-ALAS), Project Report Phase II, CTRE, ISU, April 1999.

47. Gieseman, D., N. Burdine and R. Souleyrette, Iowa DOT Weatherview, CTRE, ISU, 1999-present (web site - http://www.weatherview.dot.state.ia.us/)

46. Souleyrette, R. and Z. Hans, Iowa Traffic Safety Data Service (ITSDS) Website, CTRE, ISU, September 1999-present, (web site - http://www.ctre.iastate.edu/itsds).

45. Schuman, William G., Z. Hans and R. Souleyrette, Iowa DOT Linear Referencing System RFP, CTRE, ISU, December 1998.

44. Anderson, M.* and R. Souleyrette, GIS Traffic Planning Tools: Software, Documentation and Final Report, CTRE, ISU, December 1998.

43. Hans, Z. and R. Souleyrette, Geographic Information System (GIS) Database Development, Integration and Maintenance for the Iowa DOT Maintenance Division, CTRE, ISU/Iowa DOT Maintenance Division, December 1998.

42. Plazak, D., T. Strauss and R. Souleyrette, Improved Employment Data for Transportation Planning Final Report, CTRE, ISU, October 1998

41. Gieseman, D. and R. Souleyrette, CTAMS (Coordinated Transportation Analysis and Management System) User Tool Software and Documentation, CTRE, ISU, July 1998.

40. Gieseman, D. and R. Souleyrette, Incident Location Tool (Software), CTRE, ISU, July 1998. 39. Souleyrette, R. and D. Preissig*, Statewide Transportation Planning Model and Methodology

Development Program, Software, Data, Documentation and Phase II Report, CTRE, ISU, May 1998. 38. Schuman, W., T. Strauss, R. Souleyrette and Z. Hans, Iowa DOT GIS Implementation Plan (Strategic

Plan Update), CTRE, ISU/Iowa DOT, May 1998. 37. Souleyrette, R., T. Strauss, M. Pawlovich* and B. Estochen*, GIS-Based Accident Location and

Analysis System (GIS-ALAS), Project Report Phase I, CTRE, ISU, April 1998. 36. Location Referencing System Team Report, CTRE, ISU/Iowa DOT, January 1998. 35. Hans, Z. and R. Souleyrette, Iowa DOT Road Work Report Website, CTRE, ISU, 1998-2002. 34. Souleyrette, R., M. Kuntemeyer, D. Gieseman* and M. Anderson*, Coordination of Data Elements from

the DOT Management Systems, CTRE, ISU, May 1997. 33. Souleyrette, R. and M. Anderson*, FHWA Priority Technology Program, Final Report: Transportation

Planning GIS, FHWA-PT-96-IA (01), FHWA, U.S. DOT, February 1997. 32. Hans, Z. and R. Souleyrette, GIS Special Studies and Pilot Projects for Iowa DOT, CTRE, ISU, January

1997. 31. Souleyrette, R., et al., State of Iowa Geographic Information Systems Work Group, Iowa

Intergovernmental Information Technology and Telecommunications Plan, Dec 1996. 30. Souleyrette, R., Z. Hans and S. Pathak*, Statewide Transportation Planning Model and Methodology

Development Program, Phase I Report, CTRE, ISU, November 1996. 29. Souleyrette, R., et al., Applications for Interactive Transportation Planning GIS (TPGIS), CTRE, ISU,

May 1996. 28. Souleyrette, R., et al., GIS Strategic Plan for the Iowa DOT, CTRE, ISU, April 1995. 27. Souleyrette, R. and Z. Hans, A Review of the Transportation Components of the Disposal of Canada's

Nuclear Fuel Waste: Preclosure Assessment of a Conceptual System, for Beak Consultants, Ltd., Brampton, Ontario, Canada, February 10, 1995.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 21

26. Souleyrette, R. and Z. Hans*, High Speed Computing to Facilitate Real Time Analysis of Transportation Planning Alternatives through GIS, CTRE, ISU, September 1994

25. Souleyrette, R., Daniel R. Croce* and Z. Hans*, Use of Supercomputer for Interactive Travel Demand Modeling through GIS, CTRE, ISU/Cray Research, November 1994.

24. Souleyrette, R. and J. Jensen*, Development of Census Block - TAZ Correspondence Tables, UNLV/TRC/RR-93-02, April 1993.

23. Dilger, F. and R. Souleyrette, Data Automation in Support of the Colorado River Regional Transportation Study, UNLV/TRC/RR-93/04, City of Bullhead City, Arizona, April 1993.

22. Parentela, E.*, R. Souleyrette and D. Croce*. Traffic Data Collection, Reduction and Dissemination Program Needs Assessment, UNLV/TRC/RR-93/01, January 1993.

21. Lim, S.* and R. Souleyrette, RADTRAN Analysis for the Canadian Spent Fuel Transportation Scenarios, UNLV/TRC/RR-92/11, October 1992.

20. Yang, X.*, R. Souleyrette and E. White*, Rideshare Program User's Manual, UNLV/TRC/RR-92/10, September 1992.

19. Souleyrette, R. and S. Lim*, GIS-Based Characterization of Rail and Highway Access to Yucca Mountain, UNLV/TRC/RR-92/05, September 1992.

18. Parentela, E.*, S. Sathisan, R. Souleyrette and E. Neumann, Development of a Knowledge-Based Decision Support System, UNLV/TRC/RR-92/07, August 1992.

17. Sathisan, S. and R. Souleyrette, Recommendations for Implementation of GIS at the Nevada DOT, UNLV/TRC/RR-92/06, August 1992.

16. di Bartolo, R. and R. Souleyrette, Report of the Environmental Advisory Team on the Canadian High-level Nuclear Waste Disposal Concept, Vol. III, Technical Appendix - Transportation, for Beak Consultants Ltd., February 1992.

15. Souleyrette, R. and K. Pryor*, An Assessment of RADTRAN Capabilities and Limitations, UNLV/TRC/RR-91/03, December 1991.

14. Sathisan, S. and R. Souleyrette, GIS Applications in the Development of a Nuclear Waste Transportation Modeling System, UNLV/TRC/RR-91/06, December 1991.

13. Sathisan, S., R. Souleyrette, E. Neumann and R. di Bartolo, Transportation System Base Case Conditions (two volumes), UNLV/TRC/RR-91/04, August 1991.

12. Parentela, E.*, R. Souleyrette and S. Sathisan, Trip Generation Analysis Report: Hotels-Casinos within the Las Vegas Urbanized Area, UNLV/TRC/RR-91-01, August 1991.

11. Souleyrette, R., S. Sathisan and R. di Bartolo, Yucca Mountain Transportation Routes: Preliminary Characterization and Risk Analysis, UNLV/TRC/RR- 91/02, May 1991.

10. Parentela, E.*, R. Souleyrette and S. Sathisan, A Study of the Requirements for Modeling Bus Operations, UNLV/TRC/RR-90-03, November 1990.

9. Parentela, E.*, S. Sathisan and R. Souleyrette, Guidelines for Geometric Design and Location of Bus Turnouts, UNLV/TRC/RR-90-02, November 1990.

8. Parentela, E*, S. Sathisan and R. Souleyrette, Effectiveness of Las Vegas Boulevard Bus Turnouts, UNLV/TRC/RR-90-01, April 1990.

7. Sathisan, S., R. di Bartolo and R. Souleyrette, Functional Requirements for a Geographic Information System at the Regional Transportation Commission of Clark County, UNLV/TRC/NW-90/02, October 1990.

6. Souleyrette, R., Transportation Services and Residential Housing Construction: A Study of the Relations between Transportation and Production (Ph.D. Dissertation), William L. Garrison, Chair,

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 22

Michael Teitz and Mark Hansen, University of California, Berkeley, Dissertation Series, 1989 and University Microfilms International, 1990.

5. Souleyrette, R. and F. Robuste, TRAVEL User's Manual: Trade, Transport and Reversal - Simulated Annealing for Vehicle Routing on L-metrics, Technical Document UCB-ITS-TD-88-3, University of California, Berkeley, February 1988.

4. Robuste, F. and R. Souleyrette, CALHOP User's Manual: A Computer Program for the Routing of Vehicles with Simulated Annealing, Technical Document UCB-ITS-TD-88-2, University of California, Berkeley, January 1988.

3. Gosling, G. and R. Souleyrette, Alternative Control Strategies for Air Traffic Flow Management, University of California, Berkeley, May 1987.

2. Souleyrette, R., C.M. Walton and H. Mahmassani, Identification of Candidate Toll Roads in Current and Future Highway Development, Research Report FHWA/TX-87/23+413/1F, University of Texas at Austin, August 1986.

1. Katz, J., R. Souleyrette, et al., The Safety of Robert Mueller Airport, Policy Research Project, LBJ School of Public Affairs, University of Texas at Austin, July 1986.

ORAL PRESENTATIONS (PAPERS, POSTERS AND MODERATOR) (Note: Student co-authors indicated by asterisk * )

146. with Z. Hans and J. Brown*, “Iowa Traffic Safety Data Service,” Poster. Association of Traffic Safety Information Professionals, Traffic Records Forum, New Orleans, July 26, 2010.

145. with Z. Hans and J. Brown*, “Crash Analysis Methodologies: Software, Program, Process & Technique Review,” Poster. Association of Traffic Safety Information Professionals, Traffic Records Forum, New Orleans, July 26, 2010.

144. “Low Volume Road Crash Characteristics,” Iowa County Engineers Association Annual Meeting, Ames, IA, July 15, 2010.

143. “Railroad Engineering Program Development,” Rail Engineering Education Symposium, Overland Park, KS, June 14-15, 2010.

142. “Data for Comprehensive Highway Safety Planning – A Fresh Look,” Iowa Traffic Safety Alliance winter meeting, West Des Moines, IA, February 25, 2010.

141. “Safety of Iowa’s Low Volume Roads,” Iowa Traffic Safety Alliance winter meeting, West Des Moines, IA, February 25, 2010.

140. “Exclusive Median Bus Lanes: Seoul Experience with Suggestions and Comments on Extensibility (P10-1370),” Poster Session - Bus Rapid Transit: China, Cyprus, and Korea, TRB Annual Meeting, Washington D.C., January 12, 2010.

139. “Risk Mapping for Effective Asset Allocation: Safety Data Synergies and usRAP,” TRB’s 8th National Conference on Transportation Asset Management, Portland, OR, October 21, 2009.

138. with A. Vandervalk. “Return on Investment/ Benefit-Cost for Collecting Safety Data,” TRB’s 8th National Conference on Transportation Asset Management, Portland, OR, October 20, 2009.

137. with T. Wang*, D. Pregitzer, and K. Gkritza. “A Transportation Safety Planning Tool for the City of Ames,” TRB’s 8th National Conference on Transportation Asset Management, Portland, OR, October 20, 2009.

136. with Z. Hans, T. Jantscher* and R. Larkin*. “Horizontal Curve Identification Methodologies,” Mid-Continent Transportation Research Symposium, Ames, Aug 2009.

135. “Spatial information systems and transportation safety: road assessment programs,” Transportation Management and Policy (TMP) Colloquium, University of Wisconsin, Madison, WI, April 24, 2009.

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134. “Research Road Maps: What they are and what they should do (P09-1087),” Collaborative Development of a Research Road Map for Geospatial Information Technologies in Transportation Workshop, TRB, Washington D.C., January 11, 2009.

133. with S. Hallmark. “Integrating Behavioral, Crash and Inventory Data: Benefits from a Research Perspective (P09-1101).” TRB, Session: 369. Washington D.C., Jan 2009.

132. “Highway Safety and iRAP: The Challenge of Heterogeneous Traffic Mixes,” International Conference on Best Practices to Relieve Congestion on Mixed-Traffic Urban Streets in Developing Countries, IIT Madras, Chennai, India. Sep. 12-14, 2008. Pp. 339-348.

131. “Measuring the Highway Safety Culture,” National Safety Council Association of Traffic Safety Information Professionals, Traffic Records Forum, Session 40: Public Policy and Highway Safety: Why Decision Makers Ignore the Data, July 30, 2008.

130. “Traffic Safety Planning Tools,” Clark County Department of Public Works, Las Vegas, NV, May 12, 2008.

129. “Improving National Transportation Geospatial Information,” AASHTO GIS-T Annual Conference, Houston, TX, March 17, 2008.

128. “An Overview of Need for Geospatial Data and Outcomes from Previous Geospatial and Data Workshops” (P08-1148), Workshop, TRB Annual Meeting, Washington, D.C., Jan 2008.

127. TRB Peer Exchange Problem Statement Proposal Report to AASHTO Standing Committee on Highway Safety, Portland, Oregon, September 27, 2007.

126. Moderator, “Traffic Signals and Operations,” Mid-Continent Transportation Research Symposium, Ames, August 16-17, 2007.

125. “Assessment of Channelizing Device Effectiveness on High Speed/High Volume Roadways,” Mid-Continent Transportation Research Symposium, Ames, August 16-17, 2007.

124. “Validation and Implication of Segmentation on Empirical Bayes for Highway Safety Studies,” 4th Intl. Conference on the Impact of Environmental Factors on Health, Malta, June 2007.

123. “Travel Data Users Forum: Focus on Employment and Workplace Data - Data Users Panel,” TRB Annual Meeting, Washington, D.C., January 24, 2007.

122. “Safety Effectiveness of All-Red Clearance Intervals at Urban Low-Speed Intersections,” TRB Annual Meeting, Washington, D.C., January 23, 2007.

121. Moderator and Session Organizer: “Geographic Information System Tools for Activity-Based Travel Analysis,” TRB Annual Meeting, Washington, D.C., January 22, 2007.

120. Moderator and session co-chair, “Data and Information Technology Challenges for Safety,” TRB Annual Meeting, Washington, D.C., January 23, 2007.

119. Panelist, “Integrating Roadway, Traffic and Crash Data, TRB, Washington, D.C., Nov 2006. 118. “Road Assessment Programs: A New Approach to Highway Safety Management and

Communications,” GIS Seminar, Department of Community and Regional Planning, Iowa State University, October 2, 2006.

117. Moderator, “Traffic Safety and Operations: Work Zone Safety and Mobility,” Research Pays Off - Mid Continent Transportation Research Forum, Madison, Wisconsin, August 17, 2006.

116. “Road Assessment Programs: A New Approach to Highway Safety Management and Communications,” Research Pays Off - Mid Continent Transportation Research Forum, Madison, Wisconsin, August 17, 2006.

115. “Road Assessment Programs: A New Approach to Highway Safety Management and Communications,”32nd International Traffic Records Forum, Palm Desert, Aug 2006.

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114. “Use of Geospatial Information and Remote Sensing Data to Support Improved Roadway Access Management,” Twelfth International Conference on Urban Transport and the Environment in the Twenty-First Century, Prague, Czech Republic, July 12, 2006.

113. “Location, Location, Location,” TRB Safety Data Analysis Tools Workshop, Washington, D.C., March 27-28, 2006.

112. Panelist, Executive Scan on Improved Decision Making Using Geospatial Technology, TRB, Washington, D.C., February 28, 2006.

111. Moderator and session co-chair, “Research Issues for Implementing An All Public Road Inventory for Safety Applications,” TRB Annual Meeting, Washington, D.C., January 25, 2006.

110. “Locational Challenges for Next Generation of Crash Data Systems,” TRB Session 556 (TPS06-023), Improving Highway Safety through Crash Data Systems, Washington, D.C., January 24, 2006.

109. Moderator, “Younger Driver Issues,” Human Factors in Highway Safety Forum, University of Iowa, Iowa City, June 1, 2005.

108. “Road Safety Risk Rating: Development of a pilot US Road Assessment Program/USRAP” Iowa Statewide Traffic Records Advisory Committee Meeting, Ames, IA, March 17, 2005.

107. “Traffic and Transportation Innovations – Town Center at Jordan Creek” APWA Annual Meeting, Des Moines, IA, March 10, 2005.

106. “Older and Younger Driver Interaction in Iowa Crashes” Iowa Statewide Traffic Records Advisory Committee Meeting, Ames, IA, September 27, 2004.

105. “Effectiveness of All-Red Signal Phasing,” 9th Annual Traffic and Safety Engineering Forum, Des Moines, IA, September 2004.

104. “Change Detection to Support Planning of Traffic Monitoring,” Fall Transportation Conference, Las Vegas, Nevada, August 12, 2004.

103. With Hossein Naraghi*, “Older and Younger Driver Interaction in Iowa Crashes,” 30th International Traffic Records Forum, Nashville, TN, July 28, 2004.

102. “Improved Visualization Techniques for Crash Data,” 30th International Traffic Records Forum, Nashville, TN, July 28, 2004.

101. Moderator, “GPS and Probe Vehicles; Incident & Congestion Management,” 8th International Conference on Application of Advanced Technologies in Transportation Engineering, Beijing, China, May 27, 2004.

100. “Effectiveness of All-Red Signal Phasing,” Missouri Valley Section, Institute of Transportation Engineers, Annual Meeting, Des Moines, Iowa, April 22, 2004.

99. Moderator, “Traffic and Safety,” Mid-Continent Transportation Research Symposium, Ames, August 21-22, 2003.

98. “Process to Identify High Priority Corridors for Access Management Near Large Urban Areas in Iowa Using Spatial Data,” Mid-Continent Transportation Research Symposium, Ames, August 21-22, 2003.

97. “Spatial Data and Remote Sensing Applications in Transportation Research,” Kittelson and Associates, Inc., Broadcast from Portland, Oregon, July 14, 2003.

96. “Marketing Outside the Highway Safety Arena: Iowa's ERIS project,” 54th Annual Traffic and Safety Conference and Seminars, Columbia, Missouri, May, 2003.

95. “LIDAR Applications and Tests,” Midwest Regional Remote Sensing in Technology Workshop, National Consortium on Remote Sensing in Transportation, Madison, April, 2003.

94. “Spatial Data Systems for Road Planning and Design,” Workshop, MapIndia 2003, Delhi, India, January, 2003.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 25

93. “Designing a Traffic Monitoring Program using Landuse Change Detection,” MapIndia 2003, Delhi, India, January, 2003.

92. “GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods (poster),” TRB, January, 2003.

91. “Crash Information Systems,” Mid America Transportation Center Seminar, Omaha, NE, December, 2002.

90. “Unmanned Aerial Vehicles in Transportation Research,” Department of Civil and Environmental Engineering, Indian Institute of Technology, Madras, India, November 2002.

89. With S. Hallmark, D. Veneziano* and S. Pattnaik*, “Evaluation of LIDAR for Highway Planning, Location and Design,” Pecora 15/Land Satellite Information IV, November 2002, Denver, CO.

88. “Marketing Outside the Highway Safety Arena: A Case Study (Iowa’s ERIS project,” 28th Intl. Forum on Traffic Records and Highway Information Systems, Orlando, FL, August 2002.

87. “Using Remote Sensing Data for Access Management” (poster), TRB Annual Access Management Conference, Austin, TX, June 2002.

86. With R. Storm*, “Methods to Implement Geographic Information Systems for Validation and Reasonableness Checks of Transportation Planning Models,” 13th Annual Transportation Research Conference, CTS, Univ of Minnesota, St. Paul, MN, May 2002.

85. “Airborne LASER Swath Mapping Assessment,” Steering Committee of the National Consortia for Remote Sensing in Transportation, Santa Barbara, CA, February 2002.

84. “Systematic Identification of High Crash Locations,” TRB, National Academy of Sciences, Washington, DC, January 2002.

83. Poster and Computer Demonstration on Remote Sensing in Transportation, TRB Conference on Remote Sensing, Washington, DC, December 2001.

82. “Systematic Identification of High Crash Locations,” MOVITE, Ames, IA, October 2001. 81. “Iowa Traffic Data Safety Service,” Multidisciplinary Safety Teams Meeting (sponsored by the GTSB),

September 2001. 80. “Systematic Identification of High Crash Locations,” 6th Annual Traffic and Safety Engineering Forum,

Des Moines, IA, September 2001. 79. “Remote Sensing for Transportation Research at ISU,” TRB/NCRST Midwest Tri-State DOT

Technology Exchange Meeting, Decorah, IA, August 14, 2001. 78. “Iowa Traffic Data Safety Service,” Intl. Traffic Records Forum, New Orleans, July 2001. 77. “Transportation Applications of Advanced Geo Surface Modeling,” National Science Foundation

Workshop on Advanced Geosurficial Mapping, Gainesville, FL, July 2001. 76. “Remote Sensing Applications in Infrastructure Management,” poster presentation to Congress, Senate

Russell Building, April 17, 2001. 75. “Remote Sensing for Access Management and Collection of Inventory Elements,” National Consortium

for Remote Sensing in Transportation Conf., Gainesville, April 2001. 74. Moderator, “Traffic Safety Tools Lab,” Iowa State Traffic Accident Records Symposium, Ames,

February 2001. 73. “Transportation Safety Analysis Tools,” NHTSA National Model Conference, Des Moines, IA,

November 2000. 72. “Transportation and Society: Looking Back to Look Forward,” UNLV University Forum, October 16,

2000. (Presentation also given to UNLV ASCE student chapter.)

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 26

71. “Iowa Traffic Safety Data Service,” Iowa Traffic and Safety Engineering Forum, Des Moines, IA, October 16, 2000.

70. “Iowa State University/CTRE NCRST-I Projects,” Steering Committee of the National Consortia for Remote Sensing in Transportation, Santa Barbara, CA, October 2000.

69. “Identifying High-Crash Locations with Data Fusion,” Mid-Continent Transportation Symposium, Ames, IA, May 15-16, 2000.

68. “Iowa Traffic Safety Data Service,” Iowa Statewide Traffic Records Advisory Committee Meeting, Ames, IA, April 12, 2000.

67. Moderator, session on GIS for highway safety, AASHTO GIS-T Annual Conference, Minneapolis, MN, March 27-29, 2000.

66. “Innovative GIS Display of Crash Data,” Iowa Traffic Engineering and Safety Forum, Des Moines, IA, December 15, 1999.

65. “Spatial Data & Remote Sensing: Next Steps,” Pecora 14/Land Satellite Information III Remote Sensing Symposium and Conference, Denver, CO, December 9, 1999.

64. “Development of the Iowa Traffic Safety Data Service,” Iowa Traffic Control and Safety Association Fall Conference, Ames, IA, October 21, 1999.

63. “GIS-ALAS: Locating and Analyzing Crash Locations within a GIS Environment,” Coordinating GIS for Iowa’s Future, Iowa Geographic Information Council, Storm Lake, IA, July 28-30, 1999.

62. “Smart Maps – Crash Locations & GIS Accident Location and Analysis System (GIS-ALAS),” Region 7 Data Conference, NHTSA, Kansas City, June -10, 1999.

61. “Development of an Automated Crash Location System for Iowa,” Geographic Information Systems for Transportation Symposium, AASHTO, San Diego, CA, March 1999.

60. “A Smart-Map Methodology for In-vehicle Crash Location,” Iowa National Model for Highway Safety Conference, Des Moines, IA, December 9, 1998.

59. “A Proposed Crash Location Revision for Advantage Safety,” Statewide Traffic Records Advisory Committee, Ames, IA, October 22, 1998.

58. “Improved Employment Data for Transportation Planning,” Midwest Transportation Model Users Group, Ames, IA, September 16, 1998.

57. “Validating Freight Transportation Models,” Crossroads 2000, Ames IA, August 19-20, 1998. 56. “GIS for Transportation Asset Management in Iowa,” Transportation, Land Use and the Environment:

International, National and Local Perspectives, TRB, Seattle, WA, July 1998. 55. “Safety Data in a GIS Environment: New Tools for the Four Es,” 24th Annual International Forum on

Traffic Records and Highway Information Systems, Minneapolis, MN, July 1998. 54. “Iowa Travel Model Performance, 20 Years Later,” ASCE Urban Transportation Division National

Specialty Conference: Transportation, Land Use and Air Quality, Portland, May 1998. 53. Moderator, “GIS Applications, Challenges and Rewards,” ASCE Urban Transportation Division

National Specialty Conference: Transportation, Land Use and Air Quality, Portland, May 1998. 52. “Development and Use of Geographic Information Systems in Transportation Research and DOT

Applications,” Mid-America Transportation Center Distinguished Lecture and Transportation Series (satellite broadcast), Ames, IA, April 30, 1998.

51. “GIS ALAS, The Integration and Analysis of Highway Crash Data in a GIS Environment,” GIS for Transportation Symposium, AASHTO, Salt Lake City, UT, April 20-22, 1998.

50. “GIS-ALAS - Mapping Highway Safety in Iowa,” Governor’s Highway Traffic Safety Conference, Bettendorf, IA, March 25-26, 1998.

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49. “GIS Data Management and Distribution for Pavement Management,” Iowa Pavement Management Workshop, Ames, March 11, 1998.

48. “A GIS-T for Managing Iowa’s Transportation Assets,” TRB, Washington, DC, January 1998. 47. Moderator, Implementation of GPS/GIS Panel, Iowa County Engineer Conference, Ames, IA, December

3, 1997. 46. “GIS in Transportation Research,” Iowa Engineering Society, Ames, IA, October 23, 1997. 45. Moderator, “Iowa Transportation Applications,” Third Annual Iowa Conference on Geographic

Information Systems, Cedar Falls, IA, October 7, 1997. 44. “GIS for Transportation Research in Iowa,” Third Annual Iowa Conference on Geographic Information

Systems, Cedar Falls, IA, October 7, 1997. 43. “Introduction to GIS and GPS for County Road Maintenance,” Iowa County Road Superintendents

Conference, Ames, IA, September 25, 1997. 42. “A Desktop GIS-based Travel Demand Model for Small to Medium Sized Areas,” First Annual Iowa

Transportation Planning Conference, Ames, IA, August 26, 1997. 41. “GIS Accident Location and Analysis System,” Area 3 Annual Conference of the Highway Engineering

Exchange Program, Ames, IA, April 9, 1997. 40. “Current Traffic/Safety Research,” Iowa Traffic/Safety Engn. Forum, Grinnell, IA, April 1997. 39. “GIS Applications for Public Works,” Annual Meeting, Iowa Chapter, APWA, Ames, IA, 3/7/97. 38. “GIS Applications for County Engineering,” Annual Meeting, Iowa County Engineers Association,

Ames, IA, December 4, 1996. 37. “Statewide Freight Demand Modeling: A Multi-Commodity Layered Approach,” FHWA National

Freight Planning Applications Conference, San Antonio, TX, October 14-16, 1996. 36. “Statewide Freight Demand Modeling: A Multi-Commodity Layered Approach,” Third Annual

ASCE/Nevada Transportation Conference, Las Vegas, NV, September 1996. 35. Moderator, “Application Showcase: Public Health and Transportation,” Second Annual Iowa

Conference on Geographic Information Systems, October 8, 1996. 34. “Resources Available to Address MPO and State Technical Assistance and Research Needs,” Midwest

Regional MPO Conference, “Towards NEXTEA,” Kansas City, July 1996. 33. “GIS for the Iowa DOT,” Annual Transportation Conference, Iowa DOT, Ames, IA, March 1996. 32. Coordinator and Moderator, Session on Transportation Applications, First Annual Iowa GIS

Conference, Iowa City, IA, November 8, 1995. 31. “GIS for Analysis of Employment Data,” Iowa Department of Employment Services, Des Moines, IA,

September 11, 1995. 30. “A GIS-QRS Methodology to Develop Travel Models for Smaller Urban Areas,” Second Annual

ASCE/Nevada Transportation Conference, Las Vegas, NV, September 16, 1995. 29. “GIS-T for Locals: Past, Present and Future,” National Annual Conference of Local Technology

Assistance Programs, FHWA, Kansas City, August 7, 1995. 28. “GIS and GPS for County Engineering,” Mid-year Meeting/Conference of the Iowa County Engineers

Association, Ames, IA, July 20, 1995. 27. Moderator, session on GIS Tools, AASHTO GIS-T Annual Conf., Sparks, NV, April 1995. 26. “GIS and GPS for Transportation Engineering: A Primer,” 6th Annual Midwest Traffic Engineering and

Parking Seminar, Peoria, IL, March 30-31, 1995. 25. “Geographic Information Coordination,” Iowa Rural Dev’l Council, Des Moines, Dec 1994.

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24. “GIS and GPS for Transportation: A Primer,” Joint Annual Meeting of MOVITE and the Iowa Traffic Control and Safety Association, Des Moines, IA, November 11, 1994.

23. Session coordinator and moderator, “Geographic Information Systems,” Joint Annual Meeting of MOVITE and the Iowa Traffic Control and Safety Association, Des Moines, Nov 1994.

22. “Geographic Information Systems, Mapping Iowa’s Future,” First Iowa Conference on Highway Safety Information Systems, Waterloo, IA, November 3, 1994.

21. “GIS for Travel Demand Modeling,” MTC P.I.’s Conference, Ames, IA, August 11, 1994. 20. “Geographic Information Systems for Transportation,” Iowa Association of Regional Councils Annual

Conference, Carroll, IA, May 19, 1994. 19. “GIS at the Iowa Transportation Center,” GIS Open House, Geographic Information System Support

and Research Facility, ISU, Ames, IA, April 28, 1994. 18. “GIS Development at the Iowa DOT,” Spring Meeting of the Iowa Chapter of AM/FM International,

Amana, IA, April 20, 1994. 17. “Demonstration of Geographic Information Systems for Transportation,” Iowa DOT Annual

Transportation Fair, Ames, IA, February 25, 1994. 16. “Traffic Growth” A Self Limiting Process,” Interdisciplinary Scholars Seminar, MTC, ISU/University

of Iowa, February 11, 1994. 15. “Placarding and Signing for Hazardous Materials Shipments,” TRB Hazardous Materials Transportation

Conference, Albuquerque, NM, August 24, 1993. 14. “Organization and Time Management,” New Faculty Workshop of the PSW Section Annual

Conference, American Society for Engineering Education, Los Angeles, CA, October 16, 1992. 13. “GIS/Rail Routes for Nuclear Waste,” 5th Rail Safety Conference, Sparks, NV, July 1992. 12. “TIGER Data Improves GIS Analytical Capabilities for Studies of Nuclear Waste Transportation at

UNLV,” Second Annual Nevada State GIS Conference, Las Vegas, December 15-17, 1991. 11. “Applications of Geographic Information Systems to the Transport of Hazardous Wastes,”

Transportation Science Seminar, University of California, Berkeley, October 4, 1991. 10. “Applications of Geographic Information Systems to the Transport of Hazardous Wastes,” Center for

Advanced Transportation Research, Arizona State University, September 24, 1991. 9. “Transportation Access to Yucca Mountain: Critical Issues,” ASCE/ANS International High-Level

Radioactive Waste Management Conference, Las Vegas, NV, April 28-May 3, 1991. 8. “Geographic Information Systems in Transportation Research: State and Regional Applications,” 14th

Annual AM/FM International Conference, San Diego, March 1991. 7. Moderator, “GIS in Transportation Tract,” 14th Annual AM/FM (Automated Mapping/Facilities

Management) International Conference, San Diego, CA, March 23-27, 1991. 6. With S. Sathisan, “Geographic Information Systems Applications for State and Regional Transportation

Studies,” Annual Nevada State GIS Conference, Carson City, December 1990. 5. “The Relations between Transportation and Production,” TRB, Washington, DC, January 1990. 4. Transportation, Innovation and the Space Economy,” Annual Meeting of the Regional Sciences

Association, Santa Barbara, CA, November 1989. 3. “Transportation Services and Residential Housing Construction: A Study of the Relations between

Transportation and Production,” Trans. Science Seminar, UC Berkeley, April 1989. 2. “An Operational Typology for Toll Financing of Highway Facilities,” Annual Meeting of TRB,

Washington, DC, January 1986.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 29

1. “An Operational Typology for Toll Financing of Highway Facilities,” Winter Meeting of the District 5 ITE, College Station, TX, February 1986.

IMPACT OF RESEARCH

• Cited by 111 different organizations since 1996 (Scopus); 187 (Google Scholar) • H factor: 5 (Scopus); 8 (Google Scholar) • 41 Scopus listed publications (179 Google Scholar) • 40,000+ deployments of crash analysis and collection software • Collaborations with the University of Pisa and Indian Institute of Technology, Madras • 1,000+ small project reports and studies produced for local and state users of the Iowa Traffic Data

Safety Service • Section Chair, Data and Information Systems, National Academies Transportation Research Board

(set strategic direction for 11 TRB committees)

The table on the following page lists diversity of Scopus citation affiliations (U.S. and International Universities, U.S. and International Organizations).

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 30

U.S. Universities International Universities U.S. OrganizationsOhio State University (1) Ryerson University (4) South Carolina Geodetic Survey (1)University of Arkansas - Fayetteville (1) Huafan University (3) Gaitor Bait Software Co. (1)Johns Hopkins University (1) Inha University, Incheon (3) MCNC (1)South Carolina State University (1) University of the West Indies (3) Iowa Department of Transportation (1)Florida Gulf Coast University (1) The University of Hong Kong (2) Lawrence Berkeley National Laboratory (1)University of Hawaii at Manoa (1) Universitat Politécnica de Catalunya (2) URS Corporation (1)University of Illinois at Urbana-Champaign (2)

Technion - Israel Institute of Technology (1)

U.S. Army Aviation and Missile Life Cycle Management Command (1)

University of Maryland, Baltimore (1) Chang Gung University (2) Virginia Transportation Research Council (1)University of Washington Seattle (1) National Central University Taiwan (2) Savannah River National Laboratory (1)North Carolina Agricultural and Technical State University (1)

Instituto Tecnologico de Informatica (1)

Washington State Department of Transportation (1)

University of Tennessee, Knoxville (1) Lan Yang Institute of Technology (2) Cambridge Systematics, Inc. (1)The College of William and Mary (1) University of Al-Isra (1) Arthur Andersen (1)Morgan State University (1) Yuan Ze University (1) HNTB Corp (1)Florida Atlantic University (1) Wirtschaftsuniversitat Wien (1) KPMG Orinoco (1)Massachusetts Institute of Technology (1)

Universite Victor Segalen Bordeaux 2 (1)

National Highway Traffic Safety Administration (1)

Georgia Institute of Technology (1) University of Calgary (1) Volkert and Associates, Inc. (1)Texas A and M University (1) Ethniko Metsovio Polytechnico (1)Indiana University (1) Zhejiang University (1) International OrganizationsUniversity of South Carolina (1) Indian Institute of Remote Sensing (1) Singapore Land Authority (1)University at Buffalo State University of New York (2)

McGill University Health Centre, Montreal (1)

Greater Vancouver Transportation Authority (1)

University of Nebraska - Lincoln (1) Utrecht University (1) CHU Hôpitaux de Bordeaux (1)Clemson University (1) Hong Kong Polytechnic University (1) The Korea Transport Institute (1)Texas Southern University (1) Chang'an University (2) Lyon Associates Inc. (1)University of Southern California (1) Fudan University (1) Grontmij N.V. (1)University of Missouri-St. Louis (1) The University of British Columbia (1) Morrison Hershfield Limited (1)Michigan State University (1) Universidad Politecnica de Valencia (1) International Resources Group (1)Purdue University (6) Politecnico di Torino (1) National Defense Academy (1)UC Berkeley (5) Yuan Ze University (1)Iowa State University (4) Dokuz Eylül Üniversitesi (1)Kansas State University at Manhattan (3)Göteborgs Universitet (1)North Carolina State University (3) National University of Singapore (1)UC Davis (1) National Cheng Kung University (2)Western Michigan University (2) Beijing Jiaotong Daxue (1)Pennsylvania State University (2) Hanyang University (1)Kansas State University (2) I-Shou University (1)Northwestern Polytechnical University (2Annamalai University (1)UC Irvine (2) University of Alberta (1)Northwestern University (2) Gulbarga University (1)Wayne State University (2) Technische Universiteit Eindhoven (1)University of Texas at Austin (2) Alexandria University (1)University of Maryland (2) Al-Balqa Applied University (1)University of Alabama in Huntsville (2) Carleton University (1)University of Central Florida (2)University of Iowa (1)

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 31

PROFESSIONAL DEVELOPMENT ACTIVITIES

• American Railway Engineering and Maintenance of Way Association's (AREMA) Railroad Engineering Education Symposium (REES), Kansas City, MO, June, 2010..

• Traffic Safety Analysis Workshop (by E. Hauer), Ames IA, August 12-13, 2009 • Northwest Traffic Data Workshop, Seattle, WA, July 22, 2009 • Transportation Engineering Education workshop, Portland, OR, May 22-23, 2009. • American Railway Engineering and Maintenance of Way Association's (AREMA) Railroad

Engineering Education Symposium (REES), University of Illinois at Urbana-Champaign in Urbana, Illinois, June 8-11, 2008.

• 2008 Midwest Transportation Planning Conference, Iowa City, Iowa, June 4-6, 2008 • “Utilizing technology (visualization, simulation, interactive voting, web-based tools) to enhance

participation processes.” Humphrey Institute of Public Affairs, University of Minnesota. Held in Mankato, MN, April 10, 2008.

• ASCE Webinar, Traffic Impact Analysis, November 1, 2007 • Center for Neighborhood Technology and the Surface Transportation Policy Partnership Webinar,

“Understanding the Transportation Models and Asking the Right Questions,” September 25, 2007 • ASCE Department Heads Meeting and Workshop, Fort Collins, Colorado, May 20-22, 2007 • LIDAR Workshop, University of Northern Iowa, Cedar Falls, May 31, 2006. • Remote Sensing Workshop, University of Northern Iowa, Cedar Falls, July 27, 2005. • ArcGIS Workshop, Ames, January, 2004 • TRB Workshop on Unmanned Aerial Vehicles (UAVs), Washington, D.C., January 12, 2003. • TransCAD Travel Demand Software Training, Ames, IA, May 7-10, 2002. • National Highway Traffic Safety Administration, Workshop on Crash Records Design, Ames, IA,

January 2000. • ABET Evaluator Training, Charlotte, VA, October 1999. • ASCE Exceed Teaching Workshop, Charlotte, VA, October 1999. • Remote Sensing Workshop, Ohio State University, August 1999. • National Transit Institute, Introduction to Metropolitan Trans. Planning, Des Moines, IA, March 3-

5, 1998. • Navtech Seminars, Fundamentals of GPS I and II and Differential GPS I and II, Salt Lake City, UT,

September 1994. • Integrated Transportation Information Systems: A Strategic View, Norfolk, April 1994. • Intergraph MGE Foundations GIS Workshop, Chicago, October 10-15, 1993. • Building the GIS-T Database: An Introduction, Albuquerque, NM, March 28, 1993. • An Introduction to GIS for Transportation, Washington, DC, January 13, 1991. • Quick Response System (QRS II), Las Vegas, Nevada, December 10-12, 1990. • CEDRA Workshop (Civil Engineering Design Software), San Francisco, CA, September 28-30,

1990. • RADTRAN 4 Workshop (Nuclear Materials Transportation Impact Analysis Software), Sandia

Labs, October 1989.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 32

***TEACHING***

COURSES TAUGHT

At Iowa State University

C E 352 - Introduction to Transportation Engineering Course Description: Introduction to planning and design of highway, air, and rail transportation facilities. Technological and economic factors. Route location surveys with spirals.

C E 353 - Introduction to Railroad Planning and Design Course Description: Railroad planning and design. Operations and maintenance. Team design project. Oral and written report.

C E 354 - Introduction to Airport Planning and Design Course Description: Airport planning and design. Operations and maintenance. Team design project. Oral and written report.

C E 451/551 - Urban Transportation Planning Models Course Description: Urban transportation planning context and process. Project planning and programming. Congestion, mitigation, and air quality issues. Transportation data sources. Travel demand and network modeling. Use of popular travel demand software and applications of geographic information systems.

C E 453 - Highway Design Course Description: Introduction to traffic engineering and highway planning. Design, construction, and maintenance of highway facilities; earthwork, drainage structures; pavements. Preparation of environmental impact statement. A complete design project is required. Oral and written reports. Computer applications.

CE 515 - Railroad Engineering Course Description: Railroad industry overview, history, components. Basic track elements and design. Right of way, roadway and drainage. Signals and structures. Passenger, transit and high speed rail. Environmental conditions and permitting. Case studies, project and field trip.

C E 550 - Advanced Highway Design Course Description: Evaluation of rural and urban street and highway design theory. Establishment of design criteria, application to street and highway systems, and to intersections and interchanges; drainage design, and urban freeway design aspects. Computer applications.

C E 552 - Traffic Safety, Operations, and Maintenance Course Description: Engineering aspects of highway traffic safety. Reduction of accident incidence and severity through highway design and traffic control. Accident analysis. Legal implications. Safety in highway design, maintenance, and operation.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 33

C E 553 - Traffic Engineering Course Description: Driver, pedestrian, and vehicular characteristics. Traffic characteristics; highway capacity; traffic studies and analyses. Principles of traffic control for improved highway traffic service. Application of intersection, corridor or network analysis computer evaluation and optimization tools.

at UNLV CEE 468 - GIS Applications in Civil Engineering

Course Description: Introduction to the basics of Geographic Information Systems software and hardware and their use in civil engineering. Emphasis on the application of GIS for the planning, design, operations, and maintenance of civil engineering systems. Laboratory sessions provide hands-on experience with GIS software and hardware using specific examples/case studies of GIS applications in various areas of civil engineering.

CEG 667 - Computer Applications in Transportation Engineering CEG 760 - Urban Transportation Network Analysis and Planning CEG 795 - GIS Applications in Transportation Engineering CEG 795 - Advanced Studies in Transportation CEG 795 - Applications of Transportation Planning Models

PH.D. SUPERVISION COMPLETED

4. T. Stout, “Speed Metrics and Crash Risks – Statistical Assessment and Implications for Highway Safety Policy,” December, 2005. Now: Lecturer, Iowa State University

3. M. Pawlovich, “Evaluating Traffic Safety Resource Allocation: An Initial Framework Utilizing the Hierarchical Bayesian Philosophy,” December 2003. Now: Office of Traffic and Safety, Iowa DOT - Analyst

2. C. Monsere, (co-major with T. Maze) “A GIS-Based Multicommodity Freight Model: Model Refinement and Field Validation,” August 2001. Now: Assistant Prof. Portland State University

1. M. Anderson, “Assessing the Benefit of Improved Traveler Information: A Pseudo-Dynamic Modeling Approach,” December 1998. Now: Associate Prof. Univ. of Alabama, Huntsville

PH.D. STUDENTS IN PROGRESS

5. M. Martello, in progress (started Fall, 2010) 4. X. Chai, in progress (Toll Road Planning and Modeling) 3. J. Hochstein, in progress, expected completion, May 2011(J-Turn Expressway Intersection Simulation

and Effectiveness) 2. E. Fitzsimmons (co-major with S. Nambisan), in progress, expected completion, May 2011(Horizontal

Curve Vehicle Trajectories) 1. B. Aldemir-Bektas (co-major with O. Smadi) in progress, expected completion, December 2010 (Bridge

Management Systems and Policy)

PH.D. COMMITTEES COMPLETED

7. P. Lu, “A Statistical Based Damage Detection Approach for Highway Bridge Structural Health Monitoring.” December, 2008.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 34

6. M. Rusch, (Human Computer Interaction), “Relationships between User Performance and Spatial Ability in Using Map-based Software on Pen-based Devices,” December 2008.

5. Y. Lee, “Structural Health Monitoring System for Bridges and Components,” May, 2007 4. D. Veneziano, “Assessing Tradeoffs between Safety and Operations: An Analytical Framework,”

August, 2006. 3. A. Kamyab, “Evaluation of Automatic Vehicle Specific Identification (AVSI) in a Traffic Signal

Control System,” May 1995. 2. E. Parentela, “GIS for Radioactive Materials Routing Analysis,” May 1996. 1. K. Ackeret, “Analysis of Intersection Geometry Improvements,” May 1996.

M.S. SUPERVISION COMPLETED

Notes: Trans = interdisciplinary major in transportation; thesis option unless indicated as creative component (cc)

44. A. Shell (Trans), “Environmental Justice Case Study in the Des Moines Metropolitan Area,” May 2010. (cc) note: successfully defended in fall 2009

43. M. Caputcu, “Identification of Traffic Safety Problems and Mitigation Strategies for Low-volume Roads in Iowa,” August 2009. (cc)

42. J. Hochstein (co-major with T, Maze), “Rural Expressway Intersection Safety Treatment Evaluations,” August 2009.

41. G. Karssen, “US 18 Corridor Study, Sheldon, IA,” August 2009. (cc) 40. Z. Sun (Trans; co-major with D. Plazak), “The Use and Abuse of Crash Data in Roadway Access

Management,” August 2008. (cc) 39. J. Hinds, “The development of a case based reasoning tool for high-speed signalized expressway

intersections in the State of Iowa,” August 2008. 38. C. Mizera (co-major with O. Smadi), “Improving pavement marking performance through contrasting

new methods to quantify marking presence and increasing installation efficiencies through an evaluation of prototype bead guns,” May 2008.

37. B. Kim, “Exclusive Bus Running Ways: Overview and Applications in Seoul,” Dec 2007. (cc) 36. V. Lund, “The 70-MPH Speed Limit: Speed Adaptation, Spillover and Surrogate Measures of Safety,”

August, 2007. 35. D. Ormand, “Safety Effectiveness of Pavement Marking Retroreflectivity,” August 2007. 34. A. Chaudhari (Trans; co-major with D. Plazak), “Evaluating Traffic Impact Studies, A TIS Checklist for

Iowa,” August, 2007. (cc) 33. J. Jackson, “Effect of Spatial Data Aggregation on Highway Safety Analysis,” Dec 2006. 32. K. Park (Trans), “Employer-based Transportation Demand Management: Overview and Its Application

in Korea,” May 2006. (cc) 31. T. Knox, “Safety of High Speed Expressway Signals: a Comparison of Classical and Empirical Bayes

Method,” August 2005. 30. X. Chai, “A stabilizing mechanism for airborne video camera,” August 2005. (cc) 29. R. Tenges, “The effect of stop control on ultra low volume intersection safety,” August 2005. 28. M. DeLong (Trans), “Extracting Linear Roadway Shapes from Image Edges Using a Variation of the

Hough Transform,” August 2005. (cc) 27. H. Naraghi, “Investigating crash interaction of younger and older drivers,” December 2004.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 35

26. M. O’Brien, “Effectiveness of all-red clearance interval on intersection crashes,” Dec 2003. 25. T. Yerdelen, “Evaluation of electronic collection of vehicle crash data in Iowa,” August 2003. 24. J. Roche, “Design/Evaluation of Emergency Response Information System,” May 2002. (cc) 23. S. Veeramallu (co-major with S. Hallmark), “Applications of Remote Sensing to Highway Access

Management,” December 2001. 22. A. Gottemukkulla (co-major with K. Knapp), “Improved Data Retrieval Techniques for Crash

Analysis,” August 2001. 21. R. Storm, “Methods to Implement GIS for Validation, Reasonableness Checks and Traffic Adjustment

of Transportation Planning Models,” August 2001. 20. K. Evans, “A Statistical Analysis of Collisions in Ankeny, IA,” August 2001. (cc) 19. T. Powell (Trans), “Transportation Maintenance Costs and Urban Density,” December 2000. 18. J. Shadewald, “The Use of Travel Demand Models with Geographic Information Systems in

Transportation Planning,” December 2000. 17. M. Long, “Applications of Remote Sensing to Transportation,” August 2000. 16. B. Estochen, “An Evaluation of Medical Crash Costs: A CODES Application,” May 1999. 15. D. Preissig, “Multimodal Statewide Freight Transportation Modeling Process,” May 1998. 14. D. Gieseman (Trans), “Graphical Analysis of Roadway Sufficiency Parameters for Improved Asset

Management,” May 1998. 13. W. Vodrazka, “Travel Models for Small Urban Areas: Forensic Assessment,” December 1997. 12. J. Bhoothanath, “Use of Category Models for Pavement Management,” May 1997. (cc) 11. S. Pathak, “A GIS-based Layered Approach to Statewide Freight Transportation Modeling,” May 1997.

(cc) 10. M. Muniandi, “The Impact of Speed Limit Increase on Traffic Safety, an Analysis of Miles Traveled,

Speed and Accidents,” August 1996. (cc) 9. M. Pawlovich, “A Geographic Information System Based Accident Location and Analysis System,”

August 1996. 8. P. Mescher (Trans), “Utilizing a Multiobjective Decision Making Process in a Geographic Information

System Environment to Facilitate Bicycle Route Transportation Planning,” May 1996. 7. M. Anderson, “Quick Response Techniques to Transportation Planning: An Integrated Geographic

Information System Approach,” May 1996. 6. T. Smith (Trans), “An Information Engineering Approach for the Coordinated Development of

Statewide Multi-modal Transportation Forecasting Models,” May 1995. 5. Z. Hans, “A Geographic Information System for Transportation Modeling, Alternatives and Policy

Analysis,” December 1994. 4. P. Knight, “Evaluation of Referencing Systems for the Iowa DOT,” December 1994. (cc) 3. G. Royster (Trans), “Using Traffic Operations Software to Expand the Applicability of Travel

Forecasting Models,” August 1994. 2. J. Rasas, “Transportation Planning and Risk Assessment using GIS Models,” May 1992. 1. S. Lim, “Impact Assessment using Geographic Information Systems: Some Transportation Engineering

Applications,” December 1991.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 36

M.S. STUDENTS IN PROGRESS

- D. Cook (December 2010) - T. Wang (co-major with K. Gkritza; May 2011) - A. Loonan (Trans; May 2011.) - C. Bogenreif (May 2011) - J. Brown (Trans; co-major with K. Gkritza; December 2011)

M.S. STUDENT COMMITTEES

2010: A. Rentziou, M. Baird

2009: W. Feng (CRP) 2008: C. Sax 2007: M. Bisani, E. Fitzsimmons, D. Andersen 2006: Y. Yoo 2005: V. Binyala, M. Agarwal, W. Li (Statistics), G. Burchett, K. Kanichiro (CRP) 2004: H. Isebrands, W. Jansen 2003: S. Pattnaik, S. Harrison, D. Tebben 2002: A. Swisher, D. Veneziano 2001: J. Stribiak, K. Giese, K. Mantravadi, R. Herrick, M. Clay (Trans) 1999: H. Wu, S. Schrock 1998: J. Resler, J. Gerken, C. Cao (Trans), E. Walker (CRP) 1997: C. Monsere, T. Simodynes, R. Shanmuganathan 1995: M. Ortiz (CRP), P. Pittenger, S. Mortensen (Trans) 1994: F. Eastman (Trans) 1993: K. Helmuth, O. Kheir (Architecture) 1990: E. Parentela

STUDENT ADVISEES’ MAJOR AWARDS

• Joshua Hochstein, Ph.D., National Academies’ TRB Outstanding Paper in Geometric Design, 2009 • Thomas B. Stout, Ph.D., MTC Paper of the year 2005 • Thomas B. Stout, Ph.D., Runner Up, Philip E. Rollhaus Jr. Essay Competition, 2005 • Jerry Shadewald, M.S., U.S. DOT Regional Student of the Year, 2001 • Richard Storm, M.S., U.S. DOT Eisenhower Fellowship, 1999-2001 • Chris Monsere, Ph.D., U.S. DOT Eisenhower Fellowship, 1998-2000 • David Preissig, M.S., U.S. DOT Eisenhower Fellowship, 1996-1998 • Michael Anderson, Ph.D., U.S. DOT Eisenhower Fellowship, 1996-1999 • Michael Anderson, M.S., U.S. DOT Eisenhower Fellowship, 1994-1996

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 37

*** SERVICE***

SOCIETY MEMBERSHIP

1. American Society of Civil Engineers 2. National Academies Transportation Research Board 3. American Society for Engineering Education 4. Association of Traffic Safety Information Professionals

CURRENT PROFESSIONAL SOCIETY LEADERSHIP AND COMMITTEES National Academy of Sciences Transportation Research Board:

• Chair, Data Section ABJ00 (11 committees), 2010-present • Co-Chair (2005-2010), Secretary (1997-2005), Committee ABJ60, Geographic Information Science

and Applications, member 1995-present • Member, Advisory Panel, NCHRP 08-36/Task 100: Development of a Framework for Agency Self-

Assessment of Transportation Data Programs, 2010 • Member, Advisory Panel, NCHRP 20-07/Task 302: Value Analysis for Linear Referencing Systems,

2010 Iowa State University and University of Pisa Colleges of Engineering MOU Director (with A. Pratelli) American Society of Civil Engineers:

• Member (past Chair 2001-2007), Committee on Transportation Planning and Economics, Transportation and Development Institute, 2001 – present.

Other:

• Member, Steering Committee for the Transportation for the Nation (TFTN) Strategic Planning Effort (USDOT) and National States Geographic Information Council, 2007-present

• Fellow, Association of Traffic Safety Information Professionals (ATSIP), 2005-present. • Founder and member, Midwest Travel Model User’s Group (MTMUG), 1993-present. • Iowa Statewide Traffic Records Advisory (Coordinating) Committee, 1995-present. • Iowa Traffic Safety Alliance (formerly Safety Management System Committee), 2001-present.

PREVIOUS PROFESSIONAL SERVICE

• National Academy of Sciences Transportation Research Board Committee on Intergovernmental Relations and Policy Processes, 1991-1998.

• Midwest Transportation Consortium (MTC) Advisory Board (2002-2009) • American Society of Civil Engineers Committee on Transportation Security, Transportation and

Development Institute, 2002-2004 • American Society of Civil Engineers, Urban Transport Division, Committee on Hazardous

Materials Transportation (Secretary 1995-2002, member 1990-2002, control group 1995-2002).

• Member, Advisory Panel, "3D Design Terrain Models for Construction Plans and GPS Control of Highway Construction Equipment," Univ. of Wisconsin/CFIRE, 2009-2010.

• Iowa Statewide Traffic Records Advisory (Coordinating) Committee, Performance Measures Working group, 2009

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 38

• Peer exchange panelist, GIS for Asset Management, TRB, Charleston, WV, April, 2010. • Draft recommendations for National Commissions on Surface Transportation Policy and Revenue:

crash data collection, analysis and data sharing, AASHTO Safety Subcommittee, With J. Emery, February 2008

• Chair, Workshop on Improving National Transportation Geospatial information: Working Together for Better Decision Making, Transportation Research Board of the National Academy of Sciences, December 2007.

• Workshop Planning Committee: Advanced Geospatial Research Needs II, Transportation Research Board of the National Academy of Sciences, Irvine, California, December 2007.

• Workshop Planning Committee: Advanced Geospatial Research Needs I, Transportation Research Board of the National Academy of Sciences, Washington, D.C., Sept 2007.

• Conference Planning Committee, ASCE/TRB Conference on Air Quality, Land Use and Transportation Planning, Orlando, July 2007.

• Member, Iowa Comprehensive Highway Safety Plan (CSHP) Development Team, 2006 • Conference Planning Committee, Mid-Continent Transportation Symposium, Madison, (2006),

Ames (2005). • Iowa Safety Management Systems, ER Information System Task Force, 1999-2004. • Board of Directors, Iowa Crash Outcomes Data Evaluation System, 1998-2004. • Conference Planning Committee, Iowa Traffic Accident Records Symposium, Ames, 2001. • Governors 0.08 Task Force (Blood Alcohol Legislation Review Panel), 2000. • AASHTO/TRB/FHWA National Infrastructure Renewal Task Force, Washington, DC, 1999. • ASCE Urban Planning and Development Div, Subcommittee on GIS Applications, 93-04. • Technical Program Chair, ASCE National Specialty Conference of Transportation Planning and Air

Quality, Portland, OR, May, 1998. • Program Chair, Southwest Region Tranplan Model Users Group, Quarterly Meeting, 1992. • Organizing Committee, ITE District 6 Conference, 1992-1993. • Technical Advisory Committee, Colorado River Regional Transportation Study, 1991-1992. • Technical Advisory Committee, CA/NV Super Speed Train Commission, 1990/91. • Planning Committee, Third Annual Iowa Conference on Geographic Information Systems: “Making

the Vision a Reality – GIS Applications in Iowa,” Cedar Falls, IA, 1997. • Conference Chair, Second Annual Iowa Conference on Geographic Information Systems:

“Coordinated GIS - Enhancing the Vision,” Ames, IA, October 7-8, 1996. • Geographic Information Systems Workgroup, Iowa Intergovernmental Information Technology and

Telecommunications Task Force, 1996. • Co-organizer and Secretary, Iowa Geographic Information Council (IGIC).

Teaching-Related Service

• Preliminary development of ISU Rail Infrastructure Initiative (teaching and research) • Editorial Board, GO! Transportation Teen Magazine, 2006-present • Juror, Student and Educator of the Year Awards, Bentley Corp., Philadelphia, March 2007 • “Civil Engineering,” Career Day Presentation, Nevada, Iowa Community Schools, December 14,

2006. • Committee to redesign ISU CE Curriculum per ABET EC2000, 2000-2001 • Committee on Education, ASCE, Urban Planning and Development Division, 1996-2000. • Co-Chair, ASEE, Pacific Southwest Section Annual Conference, October 1990. • Vice Chair for Membership, ASEE, Pacific Southwest Section, 1991-1993. • Planning Committee, Iowa County Engineers Special Schools, 1997-1998.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 39

REVIEWER

Editorial Responsibilities

• Paper review coordinator, TRB ABJ60 (GIS), 2000-2005 (average 20 papers per year). • Editorial Board, Journal of Advanced Transportation, 1996-2000. • Souleyrette, R. and Shashi K. Sathisan, Editors, Journal of Advanced Transportation: Special Issue

on Geographic Information Systems Applications in Transportation Engineering and Planning, Vol. 29, No. 3, Fall 1995.

• Sathisan, Shashi K. and R. Souleyrette, Editors, The Role of New Faculty in the 21st Century, Computers in Engineering Education: Proceedings of the 1990 Annual Meeting and Conference of the ASEE Pacific Southwest Section, October 17-20, 1990, 327 pages.

Referee Services

Journals and Full Paper Conference Reviews: • 2010: TRR, Journal of the Transportation Research Board (3); TR News, Computer Aided Civil

and Infrastructure Engineering; Journal of Computers, Environment and Urban Systems • 2009: TRR, Journal of the Transportation Research Board (3); ASCE Land Use and Air Quality

Conference (2); Journal of Transport Policy; ASCE Journal of Transportation Engineering; Journal of Computing in Civil Engineering

• 2008: ASCE Journal of Transportation Engineering; ASCE Journal of Infrastructure Systems; TRR, Journal of the Transportation Research Board; ASCE AATT Conference (3); Journal of Transport Policy; Transportation Journal

• 2007: ASCE Journal of Transportation Engineering (2); TRR, Journal of the Transportation Research Board (4); Computer Aided Civil and Infrastructure Engineering; ASCE Land Use and Air Quality Conference

• 2006: ASCE Journal of Transportation Engineering (3); TRR, Journal of the Transportation Research Board (3); ASCE AATT Conference (2); Decision Support Systems Journal

• 2005: ASCE Journal of Transportation Engineering (2); ASCE Journal of Infrastructure Systems; TRR, Journal of the Transportation Research Board (5); Oxford University Press (Book Review); Computer Aided Civil and Infrastructure Engineering

• 2004: ASCE Journal of Transportation Engineering (2); TRR, Journal of the Transportation Research Board; Computer Aided Civil and Infrastructure Engineering

• 2003: TRR, Journal of the Transportation Research Board • 2002: ASCE Journal of Transportation Engineering; Environmental Modeling and Software; TRR,

Journal of the Transportation Research Board; Pergamon Press, Handbook No. 5 on Transport Geography and Spatial Systems

• 2001: TRR, Journal of the Transportation Research Board (2) • 2000: ASCE Journal of Urban Planning and Development; TRR, Journal of the Transportation

Research Board (3) • 1999: Transportation Research Journal, Part C; Photogrammetric Engineering and Remote

Sensing • 1998: Journal of the Transportation Research Forum; ASCE Journal of Transportation

Engineering (2); TRR, Journal of the Transportation Research Board • 1997: TRR, Journal of the Transportation Research Board (2) • 1996: ASCE Journal of Transportation Engineering (2); TRR, Journal of the Transportation

Research Board (4) • 1995: TRR, Journal of the Transportation Research Board (5) • 1993: Microcomputers in Civil Engineering (3)

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 40

Promotion and Tenure Case Review (blind reviews, institutions not reported to preserve confidentiality):

• 2010 • 2008 (2) • 2006 • 2000

Proposal and Report Review:

• 2010: Hong Kong Research Grants Council (2); Upper Great Plains Transportation Institute (2); University of Delaware University Transportation Center; NSF Career

• 2009: Hong Kong Research Grants Council; National Science Foundation IRES program; Mid-America Transportation Center; Academy of Finland

• 2008: Center for Complexity Science (Israel); Mid-America Transportation Center • 2007: Oregon Transportation Research and Education Consortium; FHWA • 2006: Hong Kong Research Grants Council; Harvard Univ. Program Review; Connecticut

Cooperative Highway Research Program; National Science Foundation, Transportation Proposal Reviews

• 2005: Hong Kong Research Grants Council (2); University of Wisconsin, University Transportation Center

• 2003: Hong Kong Research Grants Council (2) • 2001: Hong Kong Research Grants Council (3) • 2000: Hong Kong Research Grants Council • 1999: University of California, Berkeley, University Transportation Center • 1998: Kansas State University, Special Group Incentive Research Awards Program; ISU Ames Lab

(Department of Energy) • 1997: Oxford University Press (book proposal) • 1996: ISU Agriculture Experiment Station • 1995: New Jersey Institute of Technology University Transportation Center (4).

UNIVERSITY SERVICE

Department Committees and Leadership Positions

• Chair, Construction Engineering Senior Faculty Search Committee, 2009-2010 • Faculty Advisor, Transportation Students Association, 1996-present. • ABET Planning Team, 2008-2009 • Search Committee, CTRE Program Manager, 2008 • Associate Chair, 2007-2010 • Division Leader, Transportation, 2002-2010 • CCEE Administrative Council, 2002-present, (Chair, 2004-06) • Member, Ad Hoc Committee on Lanzhou Jiaotong Technical University / ISU CCEE Joint Program,

2004-present. • Member, Faculty Search Committee (Structures, Transportation and Construction), 2007 • Faculty Council, 2000-2002, 2006-2007 • Director of Graduate Education, CCEE, 2003-2007 • Chair, CTRE Computer Committee, 1999-2007. • Curriculum Committee, 2001-2006 (Chair 2003-2004) • Chair, Transportation Faculty Search Committee, 2001/2002.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 41

• Chair, Advising and Student Concerns Committee, 2000-2001. • Chair, Task force on Faculty Workloads and Resource Allocation, 2000-2001. • Faculty search committee, Structures Division, summer/fall 1998. • Learning-based Curriculum Task Force, 1997-2001. • CCEE Computer Committee, 1994-1998. • Moderator/host, Chi Epsilon Civil Engineering Honor Society, Mini-Conclave, March 1, 1997. • Special Events Committee, 1993-97. (Chair, 1996/1997) • TQM Strategic Planning Focus Group: Rewards and Recognition, 1995-1997. • Engineering Week Lab Instructor, September 1995, September 1997. • TQM Team, Scheduling and Access to Faculty, 1995. • Planning Committee (ex-officio), 1995. • Promotion and Tenure Review Committee, 1991-1993. • Department Incoming Student Orientation, 1991, 1992. • Student Award Selection Committee, 1992. • Entry Level Courses Review Committee, 1991.

College Committees and Leadership Positions

• MOU Development with University of Pisa, 2007 and point of contact (2007- present) • ISU College of Engineering Advancement Team (Marketing) 2008 • ISU Dean’s Committee on Research and Graduate Studies, 2003-2007. • ISU Engineering Computing Fee Task Force (Chair of Extended Access Subcommittee), 1997-2000. • UNLV College of Engineering Merit, Tenure and Promotion Evaluation Committee, 1991-1993. • UNLV College of Engineering, Tau Beta Pi Student Chapter Advisor, 1991-1993. • Faculty Search Committee for the Chair of the UNLV Computer Science Department, 1991-1993. • UNLV College of Engineering Computing Network Committee, 1992-1993. • UNLV College of Engineering, Engineering Week Lab Instructor, February 21, 1992. • UNLV College of Engineering Representative, College Fair, 1991, 1992. • UNLV College of Engineering Science and Technology Day Lab Instructor, 1990, 1991. • Faculty Search Committee for the Director of the UNLV Transportation Research Center, 1990.

University Committees and Leadership Positions

• Associate Director, CTRE, 1993-present. • College of Design Interdisciplinary GIS Certificate Program Steering Committee, 2002-present. • University GIS Facility Steering Committee, 1994-present. • Director of Graduate Education and Chair, Transportation Interdisciplinary M.S. Program, 1999-

2005 • Search Committee, CTRE Associate Director for Materials Research, 2002. • ISU/Brazil Development Team, 2001-2002. • Review of tenure application, fall 2000. • Search Committee, CTRE Director, 1999. • Proposal Reviewer, Ames Lab, fall, 1999. • Faculty Search Committee, Department of Community and Regional Planning, 1997-1998. • Mentor, Freshman Honors Program, 1994, 1998, 2007 (2). • Proposal Reviewer, Iowa Agriculture and Home Economics Experiment Station, 1996. • Search Committee for ISU GIS Facility Manager, 1996.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 42

• Transportation Engineering Curriculum Planning Committee, National Technological University, 1995.

WORKSHOPS, SEMINARS AND TRAINING SESSIONS

• “Crash Data Improvement” workshop, Montana DOT, Helena, Montana, June 2010.. • “Collaborative Development of a Research Road Map for Geospatial Information Technologies in

Transportation,” TRB, Washington D.C., January 11, 2009. • “GIS and ITS tools for improving road safety and capacity,” University of Pisa, Dec 2008. • “Use and Abuse of Crash Data for Access Management,” prepared for TRB Access Management

Conference, Baltimore, July 13, 2008. • “Crash Data Improvement” workshop, Illinois DOT, Springfield, Illinois, March 2008. • Coordinator and Instructor, Workshop on TransCAD Travel Demand Modeling, Sponsored by Iowa

DOT Office of Systems Planning, December 18, 2001. • Coordinator and Instructor, Workshop on Travel Demand Modeling, Siouxland Metropolitan

Planning Commission, February 17, 2000. • Coordinator and Instructor, Workshop on Metropolitan Transportation Planning, Bi-State Regional

Commission, January 21, 1999. • Coordinator and Instructor, Workshop on Use of Highway Capacity Software for Planners, Midwest

Transportation Model Users Group, March 30, 1998. • Instructor, Workshop on use of Statistics and Visualization, Iowa Dept. of Mgmt, 1997. • Coordinator and Instructor, MapInfo for Transportation GIS, Iowa DOT 1997. • Coordinator and Instructor, Workshop on Travel Modeling and GIS, Midwest Travel Model User’s

Group, August 1996. • Coordinator and Instructor, Tranplan Workshops for Sioux City MPO, 1996 • Coordinator and Instructor, one-day workshop on Tranplan for Beginners, January 1994. • Coordinator and Instructor, two-day workshop on Tranplan for Analysts, August 1993. • Coordinator and Instructor, two-day workshop on GIS for the Manager, August 1992. • Coordinator and Instructor, two-day workshop on TRANPLAN for Managers and TRANPLAN for

Analysts, July 1992. • Coordinator and Instructor, one-day workshop on Use of Personal Computers for Engineering and

Office Automation, March 1992.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 43

TEACHING PORTFOLIO

Appointment as Full Professor Reginald R. Souleyrette Gerald and Audrey Olson Professor of Civil Engineering Department of Civil, Construction and Environmental Engineering and Institute for Transportation Iowa State University

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 44

TEACHING PHILOSOPHY

My teaching style is collaborative. I believe learning should be the focus of good teaching, and that students must feel respected and be engaged in and outside of the classroom. I subscribe to the teaching principles set forth in ASCE’s ExCEEd method (I have taken a condensed version of the ExCEEd training), and believe there are many effective learning and teaching styles. I believe it is important to teach to all levels described in Bloom’s taxonomy of higher learning, such that data lead to information, information to knowledge, and knowledge to wisdom. Synthesis, evaluation and application are at the highest levels of learning, and should be the focus of upper division and graduate level courses. The three most important characteristics of a good teacher are 1) caring for the students, 2) up-to-date knowledge, and 3) ability to present materials/foster learning in an organized and effective manner. I see research and professional service as integral parts of the teaching/learning process and frequently attempt to bring current research as well as professionals/practitioners into the classroom. I enjoy teaching, interacting with students of varied backgrounds and experience levels, and working with other faculty to team teach or develop courses. I also enjoy relating transportation subjects to other areas of civil engineering and interdisciplinary fields as well.

DELIVERY OF MATERIAL

I believe material should be presented in various formats to meet the learning styles of various students. While some students are visual learners, all can learn from visual teaching, so I attempt to integrate interactive animations and visuals into my lectures and lab assignments. Power point and lecture are not right for all materials, but they have their place. Discussion, challenge questions, addressing students by name and learning a little about each of them, when practical, seem to be effective tools for me. I try to bring current computer applications into the lab, and make experience with them as realistic as possible (using current travel models and design projects, for example). I believe in team work, but I also believe the classroom is different than practice - some things that work in practice do not work in the classroom. Also, incentive and initiative vary with life experience, maturity and personality. Therefore, I frequently mix teams and assign individual work, to get a sense for individual aptitude and performance as well as teamwork and leadership ability.

COURSE EVALUATION (out of a 5.0 scale)

Number Title Cred Enroll Rating

2010 F CE 451/551 Urban Trans Planning and Modeling 3 22 In progress 2010 F CE 550 Advanced Highway Design (30%) w/TBS 3 15 In progress 2010 S CE 515X Railroad Engineering (50%) w/SSN 3 16 4.43 2009 F CE 451/551 Urban Trans Planning and Modeling 3 26 4.48 2009 S CE 552 Highway Safety Engineering 3 11 4.44 2009 S CE490 Independent Study 3 1 n.a. 2008 F CE 451/551 Urban Trans Planning and Modeling 3 13/3 4.46/4.67 2008 S CE 355/556 Assisted in both classes (10%) n.a. n.a. n.a. 2007 F CE 451/551 Urban Trans Plan/Mod (75%) w/PJM 3 20 4.25/4.14 2007 S CE 552 Highway Safety (60%) with Ed Kannel 3 11 4.45 2006 F CE 451/551 Urban Trans Planning and Modeling 3 21 4.44/4.89 2006 S CE 453 Highway Design (two sections) 4 27 4.31/4.43

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2005 F CE 451/551 Urban Trans Planning and Modeling 3 18 4.38/4.44 2005 S CE 550 Advanced Highway Design 3 8 4.38 2004 F CE 451/551 Urban Trans Planning (40%) w PJM 3 19 4.42 2004 S CE 453 Highway Design (two sections) 4 34 4.57 2003 F TR 555 Research Methods (30%) w Tom Maze 3(1) 12 n.a.

CE 453 Highway Design (10%) w S. Hallmark 4 35 n.a. 2003 S CE 453 Highway Design (two sections) 4 34 4.04 2002F CE 453 Highway Design (two sections) 4 41 4.12 2002S CE 453 Highway Design (90%) with Ed Kannel 4 37 4.07 2001F CE 453 Highway Design (90%) with Ed Kannel 4 35 4.50

CE 451/551 Urban Trans Plan/Mod (20%) w/ EJK 3 18 n.a. 2001S CE 486 Senior Design (10%) 3 48 n.a.

CE 453 Highway Design 4 25 4.05 2000F

CE 486 Senior Design (10%) 3 29 n.a. CE 451/551 Urban Trans Planning and Modeling 3 19 4.07

2000S CE 354 Airport Planning and Design 2 27 4.40 1999F

CE 353 Railroad Planning and Design 2 25 4.00 CE 451/551 Urban Trans Planning and Modeling 3 21 4.16

1999S CE 352-1 Transportation Engineering 3 22 4.03 CE 352-2 Transportation Engineering 3 23 4.03

1998F CE 451/551 Urban Trans Planning and Modeling 3 17 4.47 1998S CE 352-1 Transportation Engineering 3 20 4.00

CE 352-2 Transportation Engineering 3 22 4.05 1997F CE 451/551 Urban Trans Planning and Modeling 3 23 4.13

CE 553 Traffic Engineering 3 10 4.22 1997S CE 352-1 Transportation Engineering 3 31 4.00

CE 352-2 Transportation Engineering 3 26 4.00 1996F CE 451 Urban Trans Planning and Modeling 3 23 4.36

CE 553 Traffic Engineering 3 10 4.00 1996S CE 352-1 Transportation Engineering 3 23 3.80

CE 352-2 Transportation Engineering 3 30 4.10 1995F CE 553 Traffic Engineering 3 12 4.82 1995S CE 451 Urban Trans Planning and Modeling 3 14 4.75 1994F CE 553 Traffic Engineering 3 8 4.47 1994S CE 451 Urban Trans Planning and Modeling 3 12 4.55 1993F CE 553 Traffic Engineering 3 8 4.35 1993S CEG 667 Computer Apps. in Trans. Engineering 3 7 n.a. 1992F CEG 795 GIS Apps. in Trans. Engineering 3 8 4.62 1992S CEG 468 GIS Apps. in Civil Engineering 4 6 4.68 1992S CEG 795 Advanced Studies in Transportation 3 5 4.50 1991F CEG 795 Apps. of Trans. Planning Models 3 10 4.50 1991S CEG 667 Computer Apps. in Trans. Engineering 3 11 4.50 1990F CEG 760 Urban Trans. Network Anal. & Planning 3 7 4.26 1989F CEG 462 Transportation Engineering 3 7 4.84

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SAMPLE OF STUDENT TESTIMONIALS

From Course Evaluations “I learned quite a bit and it makes an eight o’clock class easier to get up for when the teacher is excited about the class” “This was the kind of CE class that I’d been waiting my entire college career for.” “This is a topic which he is passionate about and has really gotten me interested in highway safety. I thought he did a good job of incorporating new ideas and research in the class.” “Dr. Souleyrette is always a great teacher as well as a huge resource for knowledge.” “The instructor actually knows how to use the software and could teach us how to use and manipulate it. One of the few classes at ISU that actually made me want

to learn.”

“Great job. Good mix of theoretical and practical” “Best class I have taken at Iowa State” Unsolicited letters from former students “Also, I just wanted to personally thank you for urging the department to offer a Railroad Class at ISU. I use what I learn everyday and often feel up to speed with co-workers who have been working on rail projects for several years. Right now I am working on several industrial siding loops for mines, and heavily with a new high-speed passenger rail that will be connecting Madison and Milwaukee. The rail market is very exciting here in Chicago!”

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“I wanted to give you a "slice" of what is going on in my life. To be clear, much of my passion for traffic safety and the pursuit of excellence in all that I do were learned from you and Dr. Maze. In these times, my thoughts go back to ISU and I do receive much comfort, strength and guided principle from those days. It makes these issues of today that much less threatening. Thus, this is why I'm sharing this issue with you.” “I'm really enjoying this first job, and am constantly thankful for the advice you gave me and the rest of the students about the demands of a "real world" engineering job.”

GRADUATE STUDENT MENTORING/SUPPORT

The graphics below illustrate productivity in graduate funding and graduate student production.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 48

RESEARCH PORTFOLIO

Appointment as Full Professor Reginald R. Souleyrette Gerald and Audrey Olson Professor of Civil Engineering Department of Civil, Construction and Environmental Engineering and Institute for Transportation Iowa State University

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 49

RESEARCH INTERESTS My scholarship and research activities over the last 10 years fall chiefly into six categories as follows: (1) GIS in transportation; (2) remote sensing in transportation; (3) highway safety and information systems; (4) transportation planning and network modeling; (5) GIS for routing and hazardous materials transportation; and (6) traffic operations and intelligent transportation systems (ITS). I have led my team in over 150 sponsored projects with expenditures exceeding $8M as PI. We have published over 175 reviewed papers and reports and made over 130 technical presentations at symposia. My research has been sponsored by the following agencies:

• U.S. DOT o Federal Highway Administration (FHWA) o Research and Special Programs Administration o Research and Innovative Technology Administration

• Midwest Research Institute and AAA Foundation for Traffic Safety • Iowa, Minnesota, North Dakota, South Dakota, Nevada and Georgia DOTs • New York and Delaware State Police • Iowa Department of Health • U.S. DOT Bureau of Transportation Statistics • Iowa Governor’s Traffic Safety Bureau • Midwest Smart Workzone Init • Cities of Cedar Falls, Ames, Dubuque, West Des Moines, and Bullhead City • Transportation Research Board

o SHRP II o NCHRP

• Iowa Highway Research Board • US DOT Midwest Transportation Consortium • Iowa Geographic Information Council • AASHTO Pooled Funds • SAIC • Iowa Department of Economic Development • Iowa Rural Development Commission • Cray Research • US National Park Service • Regional Transportation Commission of Clark County • U.S. Department of Energy

I currently serve as chair of the Transportation Research Board’s Data and Information System Section.

Current and Future Research

Our recent research programs (groups of related projects) include the US Road Assessment Program (AAA Foundation for Traffic Safety), SHRP II S04A Geospatial Safety Database Development (TRB), NCHRP projects, Iowa Traffic Safety Data Service (Iowa Governor’s Traffic Safety Bureau and DOT), Location and analysis software for the National Model/TraCS program (various state DOTs) and National Consortium for Remote Sensing in Transportation – Infrastructure (USDOT/RITA). We are currently developing a mobile driver simulator lab for visualization of innovative highway designs (with

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 50

the National Advanced Driver Simulator at the University of Iowa) and are investigating the potential for 3D visualization for driving simulation, public perception/familiarity and for training engineers, planners and students. We are also developing a railroad engineering education program at Iowa State, and hope to follow shortly with increased sponsored research on the topic. The following self assessment was taken from my most recent (2010) post tenure evaluation.

Post-tenure Review Self Assessment/Narrative

Post-tenure review is an opportunity for self reflection and thinking about the future. Obviously, there are many such opportunities in academia, especially in a Department that continually seeks quality improvement and is moving in a positive direction as indicated by growth in student population, entrepreneurship, innovation, funded research, endowments, etc. Each year, faculty in the department complete a rigorous review of annual activity and much time is spent by colleagues on assessing this performance. The Department also continually seeks awards, and the nomination process requires much self study and review. Every major proposal requires self examination and preparation of updated resume materials. Faculty are evaluated anonymously by students in every class, and the Department Chair completes an annual review and provides feedback. Clearly, there is no shortage of opportunities for assessment, and stakeholders should feel confident that the faculty take their jobs seriously and strive to make the best use of public and private resources for the good of the students, the College, ISU, the State, and for society in general. That said, this abbreviated report focuses only on key metrics and highlights, drawing from some of the aforementioned assessments with an eye towards minimizing resources that can otherwise be best put to use continuing the activities that have impact.

In 2003, I was promoted to professor of civil engineering. In 2004, I was honored to be selected as the Gerald and Audrey Olson professor of civil engineering. I recently was reappointed to the Olson Professorship, and within the last year prepared a summary of my activities related to the Professorship. I attach my Candidate Plan for Endowed Position Funding Investments as a supplement to this post-tenure report (exhibit A). That report explains some of my past activities (since promotion) and future plans.

Activities and Accomplishments since last promotion

My principal research area is information technology, chiefly, highway safety and asset geospatial information systems. Since 1993, my scholarship production has increased, with increasing numbers of journal papers as a fraction of all work. The graphics below illustrate productivity in archived scholarship and research expenditures. I have also mentored/trained several professional staff, who have developed their own national reputation. A significant portion of funding has been dedicated to these professional and together we have established an excellent national reputation for InTrans/CTRE. In turn, this has increased the quality and experiences available for transportation graduate and undergraduate students and helped with the external visibility of ISU and CCEE. In the last 7 years, I am most pleased with the following accomplishments of the team I work with at CCEE and InTrans:

• Selection as Section Chair, Data and Information Systems, National Academies Transportation Research Board (TRB)

• Stewardship of Olson Professorship funds

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 51

• 3 years as Associate Chair during challenging budget and personnel period • Development of ISU’s role in the International and US Road Assessment Programs (FIA, World

Bank, AAAFTS, MRI) • Hiring and informal mentoring of Assistant Professor Nadia Gkritza • Working relationship with Associate Professor Chris Harding, HCI (tenured last year) • National Academies TRB funding of ISU (top in the nation), specifically accomplishments of

CTRE/InTrans team • MOU/activities with the University of Pisa • Growth and leadership at InTrans • Continued close relationship with Iowa DOT • Safety work that I hope is partially responsible for decreased death and serious injury (impact of

research/outreach) • Development of Highway Design Classroom, hiring of Lecturer Tom Stout

(note: 2010 figures for published or accepted refereed papers only)

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Plans for the future

My immediate goal is to work with transportation faculty and CCEE/COE administration to provide for growth beyond sustainability of the division’s teaching and research capacity. First and foremost I hope to contribute to the maintenance and improvement of the collegial yet challenging environment that allows our talented younger faculty to excel. It is important that they see the University and Department as a place where they are valued and needed – something I work on with them most every day. My role is as leader and mentor for these faculty, and it is critical that they see energy, creativity and enthusiasm in what I do. I intend to continue developing teams, within and outside of CCEE and the University, involving as many of the faculty and students as I can. I see InTrans as key to meeting the future budget challenges of the Department as well as providing the critical mass and learning community to continue Iowa States rise as a premier institution of transportation research, education and outreach. At InTrans, leadership positions should be filled with advanced degree holders and those with significant industry experience, to complement teaching and research capabilities of the faculty. I will continue to work towards tight integration and partnership between InTrans and CCEE, as well as mechanisms to reward outstanding performance of all our staff and students. Specifically, I have pans for several initiatives that should ideally benefit the reputation of the University. First, I intend to continue stewardship of the Olson professorship funds, leveraging these to enhance research and teaching with team-minded spirit. Second, I am working with InTrans leadership to establish CEGATS, a federally funded center of excellence for geospatial analysis in transportation safety. This program will tie together and enhance our current safety programs, especially usRAP, iRAP, Iowa Traffic Safety Data Service, and support of the Iowa Traffic Safety Alliance and State Traffic Records Coordinating Committee. Coupled with my expanded role in TRB, CEGATS will bring additional national visibility to ISU. Third, I have invested in the development of a portable driver simulator, to enable evaluation and visualization of innovative transportation designs, to educate both the public and design and safety engineers. The simulator (see photo, below) will have secondary but important benefits as we build even stronger relationships with the University of Iowa’s National Advanced Driver Simulator program (they are providing the hardware and initial software) and ISU’s Virtual Reality Applications Centers (following on my previous work with Dr. Chris Harding in the Human Computer Interaction program). Fourth, I intend to continue developing a railroad engineering program at ISU, especially in light of recent national strategic investments in rail technology and the need for greener transportation systems. A strong rail program will attract funding from both industry and national competitive sources, including programs of the National Academies and National Science Foundation. The goal is to contribute to continued increases in reputation and ranking for the Department and College, which in turn benefits fellow faculty, increases the value of the ISU diploma, and enables effective recruiting in the ever-increasingly competitive environment.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E. Page 57

Sample of Work – Exhibit B

Rural Expressway Intersection Design Guidance:

Suggestions for The AASHTO Green Book & The MUTCD

Joshua L. Hochstein (Corresponding Author)

Tom Maze (Deceased)

Reginald R. Souleyrette

Thomas B. Stout

Iowa State University Institute for Transportation

Center for Transportation Research & Education

2711 South Loop Drive, Suite 4700

Ames, IA 50010-8664

E-mail: jlhoax@iastate.edu, Phone: (515) 294-5642, Fax: (515) 294-0467

E-mail: reg@iastate.edu, Phone: (515) 294-5453, Fax: (515) 294-0467

E-mail: stouttom@iastate.edu, Phone: (515) 294-2330, Fax: (515) 294-8216

Tom Welch

Iowa Department of Transportation

Office of Traffic & Safety

800 Lincoln Way

Ames, IA 50010

E-mail: tom.welch@dot.iowa.gov, Phone: (515) 239-1267

Howard Preston

Richard Storm

CH2M HILL

1295 Northland Drive, Suite 200

Mendota Heights, MN 55120

E-mail: hpreston@ch2m.com, Phone: (651) 365-8514, Fax: (651) 688-8844

E-mail: rstorm@ch2m.com, Phone: (651) 365-8515, Fax: (651) 688-8844

Submitted: 3/8/2010

Word Count = 5,869 text + 5 tables & 2 figures @ 250 words each = 7,619 words

Hochstein et al. 1

ABSTRACT

A rural expressway is a high-speed, multi-lane, divided highway with partial access control

consisting of both at-grade intersections and grade separated interchanges. Many State

Transportation Agencies (STAs) are converting rural two-lane undivided highways into

expressways for improved safety and mobility; however, collisions at two-way stop-controlled

(TWSC) expressway intersections are reducing the safety benefits that should be achieved after

conversion. When the safety performance of these intersections deteriorates, the countermeasure

path typically begins with several signing, marking, or lighting improvements, followed by

signalization, and could ultimately result in grade separation. Signals aren’t always effective at

improving safety and hamper the mobility expressways are meant to provide. Interchanges are

not economically feasible at every problematic intersection and can take years to develop;

therefore, more design options at TWSC rural expressway intersections are needed.

Some STAs have experienced success with innovative rural expressway intersection

countermeasures which are not currently included as design options within national guides.

Therefore, NCHRP 650, ―Median Intersection Design for Rural High-Speed Divided Highways‖

was commissioned to recommend revisions to AASHTO’s ―A Policy on Geometric Design of

Highways and Streets‖ (Green Book) and the ―Manual on Uniform Traffic Control Devices‖

(MUTCD) regarding rural expressway intersection design. The project tasks included

summarizing existing expressway intersection design guidance within these national guides,

documenting STA experience with innovative rural expressway intersection safety treatments,

and recommending revisions to the Green Book and the MUTCD. The results of this work are

summarized in this paper, focusing primarily on the suggested Green Book and MUTCD

modifications.

Key Words: Rural expressway intersection safety—Median intersection design—AASHTO

Green Book—MUTCD

Disclaimer: This research was conducted as part of National Cooperative Highway Research

Program (NCHRP) Project 15-30, soon to be published as NCHRP Report 650.

The opinions and conclusions expressed or implied in this paper are those of the

research agency that performed the research and are not necessarily those of the

Transportation Research Board (TRB), the National Academies, or the program

sponsors.

Hochstein et al. 2

INTRODUCTION

A rural expressway is a high-speed, multi-lane, divided highway with partial access control

which may consist of both at-grade intersections and grade separated interchanges. As a result of

the trend to convert rural two-lane undivided highways into expressways, rural expressways are a

rapidly growing component of the nation’s transportation network (1). As these facilities

experience growth in traffic, at-grade intersection collisions begin to reduce the safety benefits

that should be achieved as a result of conversion (2). When the safety performance of an at-

grade intersection begins to deteriorate, the traditional reactive approach taken by many STAs is

to consider improvements at that time. Often, the typical countermeasure application path shown

in Figure 1A starts with several signing, marking, and/or lighting improvements, followed by the

implementation of traffic signals, and could ultimately result in grade separation (although the

extremely high cost of right-of-way makes this option unlikely in many cases). However,

highway designers need other options because interchanges take many years to develop, during

which time the crash problem may continue, and their high cost limits their use on expressways.

Furthermore, TWSC rural expressway intersections often experience safety problems long before

traffic signal volume warrants are met (if ever), signals hamper the mobility expressways are

meant to provide, and they don’t always improve safety as intended since they are not expected

in rural areas (3).

Far-side right-angle collisions (i.e., right-angle crashes involving left-turning or crossing

minor road vehicles which successfully cross the first (near-side) set of expressway lanes, but

collide with expressway traffic in the second (far-side) set of lanes after traversing through the

median) are the predominant crash type at conventional TWSC rural expressway intersections (4,

5). The underlying cause of these collisions, in most cases, is the inability of the driver, stopped

on the minor road approach or in the median, to judge the arrival time of approaching

expressway traffic (4). Therefore, eliminating the far-side intersection conflict points and/or

assisting minor road drivers with gap (or more correctly, lag – time remaining to arrival of next

vehicle) selection are critical to improving safety at TWSC rural expressway intersections.

Currently, there is a shortage of design options within AASHTO’s ―A Policy on

Geometric Design of Highways and Streets (6)‖ (Green Book) and the ―Manual on Uniform

Traffic Control Devices (7)‖ (MUTCD) which address conflict point management or gap

selection; therefore, NCHRP 650, ―Median Intersection Design for Rural High-Speed Divided

Highways (8)‖ was commissioned to recommend revisions to the Green Book and the MUTCD

regarding intersection design on rural high-speed (50 mph and faster) divided highways with

partial or no control of access (expressways). The tasks of this research project included: 1)

summarizing the existing design guidance within these national guides and identifying current

limitations, 2) a literature review and survey of STAs to identify and evaluate alternative median

intersection design treatments, 3) recommending changes to the Green Book and the MUTCD

based on the findings of the first two tasks, and 4) identifying areas warranting future study. The

results of this work are summarized in this paper.

EXISTING POLICY SUMMARY

AASHTO Green Book Review

The 2004 AASHTO Green Book (6) is intended to be a comprehensive reference manual for the

planning and geometric design of highways and streets. The policies recommended in this text

Hochstein et al. 3

are based on established design practices which are supported through research. The guidelines

are meant to produce highways and streets which are safe, comfortable, convenient, and

operationally efficient for users, acceptable to non-users, and in harmony with the surrounding

environment. Cost-effective design is emphasized while permitting sufficient design flexibility

to encourage independent designs tailored to particular situations. The Green Book is organized

into ten chapters which stress the relationship between highway design and highway function.

Design guidelines are included for freeways, arterials, collectors, and local roads, in both urban

and rural settings, paralleling the functional classifications used in highway planning.

A rural expressway is functionally classified as a rural arterial; therefore, based on this

classification, the design guidance for rural expressways and their intersections should be

contained in Chapter 7, ―Rural and Urban Arterials‖. However, the existing geometric design

guidance for rural expressways and rural expressway intersections is scattered throughout the

Green Book as shown in Table 1. Guidance specific to expressway design resides in Chapter 4

―Cross Section Elements‖, Chapter 7 ―Rural and Urban Arterials‖, Chapter 8 ―Freeways‖,

Chapter 9 ―Intersections‖, and Chapter 10 ―Grade Separations and Interchanges‖ with the

majority of the existing design guidance located in Chapters 7 and 9.

Chapter 4 includes a small section on median and frontage road design. Chapter 7

contains a broad range of information regarding rural divided arterials and their intersections

including the development of an expressway corridor, access management, cross-section

elements, signalization, and wrong-way entry prevention. Chapter 9 discusses intersection

design, but does so in a very general sense by addressing intersection design for all types of

facilities. Specific to divided highways, Chapter 9 discusses median design for typical four-

legged intersections as well as the use of offset left-turn lanes, indirect left-turns via jughandles,

indirect lefts via median U-turns, and intersection design with frontage roads. Furthermore,

Chapter 9 provides other general intersection design guidance which, although not specific to

expressway intersections, may be applicable in their design. In addition, Chapters 8 and 10 may

be used to design the major features of a rural expressway and to help decide whether an

intersection or an interchange is desirable at a particular crossing.

MUTCD Review

The 2003 Edition of the MUTCD with Revisions Number One and Two Incorporated (7),

dated December 2007, was the version in use by practitioners at the time of this study. The

MUTCD is published by FHWA and defines the minimum standards to be used by road

managers nationwide for installing and maintaining traffic control devices on all streets and

highways. Public agencies across the nation rely on the MUTCD to provide guidance ensuring

that all traffic control devices are understandable, recognizable, visible, and uniform in size,

shape, color, and placement. The success of the MUTCD depends on nationwide acceptance and

application. Consequently, each state is required to adopt the MUTCD as their own standard or

have a State MUTCD which is in substantial conformance with the national guide. The speed

with which technology, traffic control, and traffic operations change makes the MUTCD a

dynamic document which continuously evolves in order to reflect the most recent innovations;

therefore, input from practitioners and all other stakeholders in developing and evaluating the

contents of the MUTCD is critical in keeping the guide current and relevant. With this in mind,

the purpose of this section is to document the existing guidance for the signing and marking of

TWSC rural expressway intersections.

Hochstein et al. 4

The MUTCD (7) is comprised of ten parts, all of which were initially considered in the

review. However, the evaluation predominantly focused on the information contained within the

first four parts since the final six parts have little to do with the focus of this research. The

specific rural expressway at-grade intersection signing, marking, and traffic control guidance

which was found within Parts 1-4 is cataloged in Table 2; however, there is additional general

guidance in these parts that could also be applied at rural expressway intersections.

The majority of MUTCD guidance relative to expressway intersections can be found in

Part 2, ―Signs‖. This part describes guidelines for the application of regulatory, warning, and

guide signs depending on the particular location (rural or urban) and type of roadway (freeway,

expressway, conventional road, or special purpose road) upon which they are to be used. Section

2A.23 establishes that divided highway intersections should be signed as two separate

intersections when the median width is 30 feet or greater. MUTCD Figures 2B-10 and 2B-13

through 2B-15 provide standard regulatory signing and marking plans for divided highway

intersections. Chapter 2E discusses the intent and application of guide signs on freeways and

expressways; however, the majority of Chapter 2E details the guide signing requirements for

interchanges and there is actually very little information describing the guide signing

requirements for at-grade intersections on expressways. In fact, Section 2E.26, ―Signs for

Intersections At-Grade‖, states, ―If there are intersections at-grade within the limits of an

expressway, guide sign types specified in Chapter 2D (Guide Signs – Conventional Roads)

should be used; however, such signs should be of a size compatible with the size of other signing

on the expressway.‖ Of the guide signs described within Chapter 2D, there is only one which is

specifically meant for use at divided highway intersections. That sign is the CROSSOVER (D-

13 Series) sign shown in MUTCD Figure 2D-12 and MUTCD guidance states that this sign

―may be installed on divided highways to identify median openings not otherwise identified by

warning or other guide signs.‖

ALTERNATIVE MEDIAN INTERSECTION TREATMENTS

In general, rural expressway intersection safety treatments can be divided into three broad

categories: conflict point management techniques, gap selection aids, and intersection

recognition devices. Conflict point management techniques are those treatments which

remove/reduce, relocate, and/or control the 42 conflict points which occur at a traditional TWSC

rural expressway intersection. Gap selection aids are those countermeasures which are intended

to aid a driver in selecting a safe gap into or through the expressway traffic steam. Finally,

intersection recognition devices are countermeasures which are intended to enhance intersection

conspicuity for either minor road or expressway drivers. Table 3 provides a categorized listing

of numerous rural expressway intersection safety treatments compiled from the literature review,

including two previous surveys of STAs (1, 9).

Ten of the most promising rural expressway intersection safety strategies highlighted in

Table 3 were selected for further study by the NCHRP 15-30 Project Panel members. The

screening process was based on a survey of STAs regarding what alternatives they have

implemented and the level of success they perceived/experienced. With that information the

most promising strategies were selected and discussed. The project panel reviewed and

concurred with the "ten most promising strategies." Further study involved conducting ―case

studies‖ to document the design and safety experience of STAs who have experimented with

those strategies.

Hochstein et al. 5

The ten case studies investigated J-turn intersections, offset T-intersections, jughandle

intersections, Intersection Decision Support (IDS) technology, static roadside markers, left-turn

median acceleration lanes (MALs), offset right-turn lanes, offset left-turn lanes, enhanced

intersection guide signing, and dynamic advance intersection warning systems. Before and after

crash data were obtained and naïve before-after safety evaluations were performed for seven of

the ten treatments examined (no data were available for the other three). Most of these

treatments resulted in improved overall safety and/or a reduction in the targeted crash types.

However, a limited number of sites were examined and, in some cases, the number of before and

after crash data were inadequate to perform any statistical evaluation. Furthermore, the naïve

before-after analysis methodology did not take regression-to-the-mean into account and it is not

known exactly what part of the noted change in safety can be attributed to the treatment and what

part may be due to changes in other external factors (10). Therefore, according to the NCHRP

500 Series (11) definition, these intersection treatments are still considered to be either ―tried‖ or

―experimental‖ and should be properly evaluated in order to move them into the ―proven‖

category. Nevertheless, the case studies revealed that there are promising safety treatment

options for TWSC rural expressway intersections which are not currently described in the Green

Book (6) or the MUTCD (7). These treatments address conflict point and gap selection issues

while avoiding signalization and grade separation and help to set the stage for the development

of a richer set of rural expressway intersection countermeasures as shown in Figure 1B.

RECOMMENDATIONS

Green Book Recommendations

A thorough evaluation of the design guidance for TWSC rural expressway intersections

contained within the 2004 AASHTO Green Book (6) was conducted in an attempt to identify

areas where the existing guidance might be lacking. For example, the Green Book describes

dimensions for turn lanes, corner radii, and median noses, but no indication is given as to how

these features contribute to safety. On the other hand, there is no design guidance describing

how to restrict median access, but there is a great deal of information relating access and safety.

As a result, limitations were identified and recommendations for potential Green Book revision

were separated into three general categories: organizational changes, philosophical changes, and

design guidance updates. The suggested changes within these three areas are summarized in

Table 4 and briefly described here.

Organizational Changes

In the 2004 AASHTO Green Book (6), design guidance for rural expressways and their

intersections is spread throughout several chapters as illustrated in Table 1 (Chapters 4, 7, 8, 9,

and 10) which may create confusion for roadway designers. This is likely due to the fact that

expressways are a hybrid design between a rural freeway and a conventional two-lane undivided

rural arterial. As such, roadway designers are faced with a choice between using Chapter 7,

―Rural and Urban Arterials‖ or Chapter 8, ―Freeways‖ when designing a rural expressway.

Similarly, when designing rural expressway intersections, designers must simultaneously

consider information contained in Chapters 4, 7, 9, and 10. Redundancy and confusion may

result; thus, revised Green Book organization is recommended.

Hochstein et al. 6

An ideal solution to this problem would be to add the universally familiar term

―expressway‖ to the basic functional classes and reorganize the Green Book so that all material

on rural expressways and rural expressway intersections is included in a single comprehensive

chapter as has been done for freeways (Chapter 8). Like freeways, expressways are not

considered a separate functional class of roadway, but they have unique geometric criteria which

demand a separate design designation apart from other arterials. However, members of the

AASHTO Technical Committee on Geometric Design have expressed concern over this

reorganization, noting that it would be a tremendous undertaking while the modifications might

not address all of the issues and may create other confusion in using what is already a

cumbersome guide and reference manual. Alternative reorganization strategies may be to

include all information on rural expressway intersection design as a separate section within

Chapter 9, ―Intersections‖ or organizing intersection design issues based on the speed of the

major approach.

Although it is suggested that, at a minimum, Chapter 9 of the Green Book be revised to

include a separate section on expressway intersection design, a more realistic approach may be to

create a separate complementary manual for expressway design similar to ITE’s ―Freeway and

Interchange Geometric Design Handbook‖ (12) which serves as a companion to the Green Book

and presents fundamental concepts and practices related to freeway and interchange design

commensurate with state-of-the-art practice. Once this ―Expressway and Expressway

Intersection Geometric Design Handbook‖ becomes mature, the most essential information it

contains could be incorporated into the Green Book.

Philosophical Changes

The current Green Book philosophy attempts to integrate the highway planning and design

processes by utilizing the functional classification of a roadway facility as well as the anticipated

design year traffic volume and composition to select a design level-of-service, which has an

influence on design criteria. The goal is to design the facility, without overbuilding it, so that it

will be able to provide and sustain a desired minimum level-of-service throughout its design life.

Safety is implied, but not explicitly considered in this process. For example, TWSC rural

expressway intersections tend to experience safety issues long before they experience

congestion. Four-lane expressway corridors tend to become congested around 45,000 vehicles

per day (vpd); however, the safety performance of expressway intersections deteriorates at far

lower mainline volumes (around 22,000 vpd in Minnesota). In addition, due to unanticipated

adjacent land development and changes in travel patterns rural expressways create, intersection

volumes can be more difficult to predict. As a result, rural expressway intersections can develop

safety and operational issues before such problems reach a corridor-wide level.

Chapter 7 of the Green Book currently contains a section regarding planning

considerations for the ultimate development of four-lane divided rural arterials. Although this

section does mention the need to acquire additional right-of-way for future intersection

improvements, it does not address planning for specific intersection modifications which may be

required before the end of the design or functional life of an expressway corridor. When the

safety performance of an at-grade expressway intersection begins to deteriorate, the usual

approach is to consider countermeasures at that time. This philosophy is reactive and

problematic as countermeasures may take years to develop while the safety issues continue to

occur.

Hochstein et al. 7

Two states, Illinois and Missouri, employ a more proactive intersection safety planning

process with loose triggers defining when to start planning for or constructing the next level of

intersection design. On expressways, the Illinois Department of Transportation (IDOT) uses

traffic signal volume warrants to define the need for an interchange or the need to plan for future

interchange development during the corridor planning process (13). On the other hand, the

Missouri Department of Transportation (MoDOT) has developed minor road volume thresholds

and other subjective ratings which help them to select between six different levels of expressway

intersection design alternatives (14). Of course, specific site conditions and crash history should

also be considered, but these additional design options help to bridge the gap between an

ordinary TWSC expressway intersection and an interchange. This approach allows DOT

funding to be stretched to address other system needs when an interchange isn’t truly necessary.

Therefore, the Green Book (6) should advocate a more proactive expressway intersection safety

planning process with suggested triggers defining when to start planning for or constructing the

next level of intersection design as a TWSC intersection transitions into a full interchange over

the course of its life cycle as shown in Figure 1B. However, in order for this recommendation to

be implemented, more research is necessary to develop guidelines (volume or crash

frequency/rate based) for the conditions under which each alternative intersection design should

be considered and would be expected to fail in terms of both safety and operations.

In addition, expressway intersection safety should be more actively considered during the

initial expressway corridor planning/development process through the strategic placement of

intersections on tangent sections, the reduction of intersection skew, and improved access control

through the use of frontage roads, offset T-intersections, and J-Turn intersections along the

corridor. Partial access control on expressways should include limiting access density as well as

carefully placing access locations. For example, expressways are typically built as bypasses

around small rural communities and at-grade intersections tend to be placed on horizontal curves

where the mainline alignment shifts to avoid the town. Although more research is necessary to

quantify the impact of horizontal curvature on expressway intersection safety, their presence on

the mainline seems to create more problems for minor road drivers in judging the arrival time of

oncoming expressway vehicles. Similarly, other features such as intersection skew and

independent vertical expressway alignments tend to make it more difficult for minor road drivers

to select safe gaps. Therefore, roadway designers should work diligently during corridor

development to avoid placing intersections where these features exist. Furthermore, in rural

areas, numerous field entrances are typically requested by landowners. Instead of allowing

multiple access points along the expressway, frontage roads should be used as collectors to lead

traffic to a single expressway intersection, thus preserving the through character of the

expressway.

Design Guidance Updates

Perhaps the most important recommended update to the Green Book is to include design

guidance for the rural expressway intersection types which eliminate or reduce far-side conflict

points (J-turn intersections and offset T-intersections) or those which address the issue of gap

selection for minor road drivers (median acceleration lanes and offset right-turn lanes). Within

Chapter 9, the current edition does a good job describing the design of traditional four-leg or

three-leg stop-controlled rural divided highway intersections. The existing guidance describes

determining adequate intersection sight distance (ISD), designing median openings to

accommodate turning paths for left-turn exit and entry, and designing auxiliary deceleration

Hochstein et al. 8

lanes. However, minor road driver gap selection issues and the associated far-side right-angle

crash problem are not discussed in relation to these intersections. Furthermore, when

conventional intersection designs start to experience safety and/or operational problems,

roadway designers are only given design guidance for a few corrective intersection alternatives.

These options include offset left-turn lanes, indirect left-turns via jughandles, indirect left-turns

via median U-turns, and constructing an interchange. Of the first three, only the median U-turn

intersection design partially addresses the gap selection issue for minor road drivers and the

Green Book currently discourages the use of a J-turn type intersection on high-speed roadways.

Moreover, the existing design guidance provided for offset lefts, jughandles, and median U-turns

is limited. Therefore, the design guidance provided for these three alternatives should be

expanded to reflect current STA practice and, based on the preponderance of right-angle crashes

occurring at TWSC rural expressway intersections, it should be a priority to include median

intersection design options which address the issue of gap selection for minor road crossing and

left-turn maneuvers in the next edition of the Green Book. Currently, little or no design guidance

is available regarding J-turn intersections, offset T-intersections, median acceleration lanes, or

offset right-turn lanes. Consequently, few STAs are using these designs. Once more research

has been conducted, the Green Book should eventually include information on the safety effects

of each alternative design option and include guidelines addressing the conditions under which

each design might be implemented.

MUTCD Recommendations

A thorough evaluation of the MUTCD (7) was conducted regarding the signing, marking, and

traffic control devices used at TWSC rural expressway intersections to identify areas where the

existing guidance might be insufficient. The MUTCD identifies a number of signs and markings

for improving driver recognition of approaching intersections (over size signs, flashing lights,

advance warning signs, pavement messages, etc.), but there is no mention that intersection

recognition is less of a contributing factor in intersection crashes than gap recognition and

selection, for which no discussion is provided and no devices are identified. In general,

opportunities for MUTCD revision were separated into three categories: assistance for minor

road drivers, assistance for expressway drivers, and other technical modifications. The

recommendations within these three areas are summarized in Table 5 and briefly described here.

Assistance for Minor Road Drivers

Currently, the MUTCD (7) identifies a number of signs and markings which are intended to help

a minor road driver recognize an approaching stop-controlled intersection. These devices seem

to be effective at TWSC rural expressway intersections given the relatively small proportion of

―ran-the-stop sign‖ collisions (4). However, based on the over-representation of right-angle

―failure-to-yield the right-of-way‖ crashes associated with gap selection at these intersections, a

primary enhancement to the current MUTCD guidance would be to identify any traffic control

devices or markings that are intended to assist minor road drivers with their decision-making

processes for judging and selecting safe gaps in the expressway traffic stream. Currently, the

MUTCD does not address the need for or the application of such devices and/or markings. Even

though there is no widely accepted device to assist with gap selection from the minor road, there

have been attempts to develop and deploy experimental systems such as Intersection Decision

Support (IDS) technology, static roadside markers, median pavement markings, and median

Hochstein et al. 9

signage. These devices are meant to inform minor road drivers of the size and availability of

gaps in expressway traffic, encourage a two-stage gap selection process, and/or remind them to

look again before proceeding. The MUTCD should provide some guidance and uniformity for

the use of such devices as experimental treatments or as accepted practice after their

effectiveness has been sufficiently proven.

Assistance for Expressway Drivers

Another enhancement to the MUTCD (7) would be to include language supporting the use of

intersection recognition strategies on the expressway approaches (i.e., freeway-style guide signs,

diagrammatic guide signs (see Figure 2), dynamic warning signs and flashers, intersection

lighting, or other such devices) to help expressway drivers identify TWSC intersections with a

higher crash risk. The relative safety of an intersection depends on many factors; but skewed

intersections, intersections where the mainline is on a horizontal or vertical curve, intersections

with high minor road volumes, intersections with extreme hourly peaking on the minor road, or

intersections with some combination of the above tend to have higher crash frequencies/rates/

severities (5). These characteristics seem to make it more difficult for minor road drivers to

select safe gaps. Although this strategy would not aid minor road drivers in this regard, it would

alert the expressway driver to the increased potential for conflict so that they might be prepared

to take evasive action, if necessary, should a minor road driver select an unsafe gap. This

information would also allow expressway drivers to be more aware of traffic leaving the

expressway.

Existing MUTCD guidance for intersection warning signs (Section 2C.37) suggests that

advance intersection warning signs may highlight the relative importance of the intersecting

roadways by using different widths of lines on the symbol; however, there is no existing

guidance for differentiating the relative importance of one intersection versus the next. On the

other hand, the existing guidance for expressway at-grade intersection guide signing (Section

2E.26) simply instructs the user to use the intersection guide signing specified in Chapter 2D

(Guide Signs – Conventional Roads). Of the guide signs described in MUTCD Chapter 2D,

many have likely application at rural expressway intersections; however, only the CROSSOVER

(D-13 Series) signs shown in MUTCD Figure 2D-12 (Figure 2A) are specifically meant for use

on divided highways. Section 2D.51 of the MUTCD (7) states, ―Crossover signs may be

installed on divided highways to identify median openings not otherwise identified by warning

or other guide signs.‖ The only further guidance given to the user is that this signing should be

consistently sized with other signing along the expressway. The Crossover signs are essentially

freeway-style guide signs which could be placed to help expressway drivers identify TWSC

intersections with a higher crash risk (as in Figure 2A).

Section 2E.26 of the MUTCD also provides the option that ―Advance guide signs for

intersections at-grade may take the form of diagrammatic layouts depicting the geometrics of the

intersection along with essential directional information.‖ However, no examples of

diagrammatic signing for at-grade expressway intersections are currently provided in the

MUTCD. The Nebraska Department of Roads has used one potential version of this type of

signage as shown in Figure 2B and such examples (or variations thereof) should be provided in

MUTCD Section 2E.19 or 2E.26. Another recommendation is to provide typical at-grade

expressway intersection guide signing plans in MUTCD Section 2E.26 rather than directing

users to the section for guide signs on conventional roads.

Hochstein et al. 10

Furthermore, the MUTCD guidance in Section 4K.03 states that warning beacons are

typically used on approaches to intersections where additional warning is required or where

special conditions exist; however, the use and application of dynamic intersection warning

systems (i.e., ―Vehicles Entering When Flashing‖ signs) are not described. In addition, the

MUTCD provides no guidance as to when a highway agency should consider this type of

advance intersection signage. Therefore, more research is necessary to develop traffic volume,

crash experience, or other guidelines indicating when an agency should consider enhanced

advance warning or guide signing along the expressway approaches at TWSC rural expressway

intersections.

Other Technical Modifications

A number of technical modifications to the existing MUTCD (7) guidance are suggested. These

modifications are listed in Table 5 and are possible without any further research or development.

The modifications can be grouped into three areas: figure additions, figure modifications, and

addressing inconsistencies between the MUTCD and the Green Book.

Currently, MUTCD Figures 2B-10, 2B-13, 2B-14, and 2B-15 illustrate regulatory signing

and pavement marking plans for divided highway intersections. These four figures represent

three conditions: 1) medians at least 30 feet wide and conventional left-turn lanes (Figures 2B-

10 and 2B-13), 2) medians less than 30 feet and conventional left-turn lanes (Figure 2B-14), and

3) medians less than 30 feet and offset left-turn lanes (Figure 2B-15). However, there are no

figures representing the condition of medians at least 30 feet wide and offset left-turn lanes.

Signing and pavement markings for this condition were recommended by Staplin et al. (15) and

should be incorporated into the MUTCD. There is also lack of a figure showing WRONG WAY

signing, as shown in Figure 2B-10, where the median width is less than 30 feet. The lack of such

a figure implies that the WRONG WAY signing is not necessary or is optional for medians less

than 30 feet wide, when in fact the text guidance in MUTCD Section 2B.34 states, ―The DO

NOT ENTER sign shall be used where traffic is prohibited from entering a restricted roadway‖

and there is no reference to median width as a condition of application. If the WRONG WAY

signing application or placement does not depend on median width, then the median width

qualification should be removed from Figure 2B-10. The MUTCD also lacks standard plans for

warning and guide signing along TWSC rural expressway intersection approaches. These could

be included in the next version of the MUTCD along with enhanced warning and guide signing

plans for higher crash risk/critical intersections. Future figure additions to the MUTCD could

also include standard signing and marking plans for non-traditional rural expressway intersection

designs such as the J-turn intersection, offset T-intersections, median acceleration lanes, and

offset right-turn lanes. Signing standards for these non-traditional expressway intersection

designs are necessary for nationwide uniformity and should be based on the experience of STAs

who have already experimented with these designs and developed their own standard signing

plans.

A second set of technical modifications involve making some slight changes to the

existing MUTCD figures illustrating signing and marking plans for TWSC rural expressway

intersections. Each of the existing four MUTCD figures (2B-10, 2B-13 through 2B-15) has

minor problems and there is an overall lack of consistency between these figures. Figures 2B-10

and 2B-14 show where the median width is measured based on the MUTCD definition, but

Figures 2B-13 and 2B-15 do not show this dimensioning. Figure 2B-10 does not depict a double

yellow centerline or stop bars within a wide median as shown in Figure 2B-13. Figures 2B-14

Hochstein et al. 11

and 2B-15 do not include the option for YIELD signs or YIELD bars in a narrow median even

though a passenger car may be fully stored within a 25 foot median area according to the Green

Book. Figure 2B-15 illustrates negatively offset left-turn lanes which do not provide enough

intersection sight distance for left-turners when opposing left-turn vehicles are present as

established in previous research (15, 16). This figure may explain our observation that some

STAs are constructing offset left-turn lanes in this manner. Therefore, the offset left-turn lane

geometry in this figure should be changed to illustrate positively offset left-turn lanes as defined

in McCoy et al. (16). In addition, the term ―offset‖ should appear in the figure title rather than

the word ―separated‖ in order to be consistent with the AASHTO Green Book (6). Finally,

because Figures 2B-10 and 2B-13 both show regulatory signing plans for TWSC rural

expressway intersections with medians 30 feet or greater and conventional left-turn lanes, these

figures could be combined into one standard regulatory signing and marking plan for this

condition. Such a figure would relieve any confusion on how to properly place the ONE WAY

signing in conjunction with the WRONG WAY signage. Similar standard full regulatory signing

plans could also be included for each of the other three median width and left-turn lane type

combinations.

The final technical suggestion involves clearing up inconsistencies which exist between

the Green Book and the MUTCD. Inconsistencies in the median width definition and the

minimum median storage requirements specified in the Green Book and the MUTCD should be

made to coincide. Section 1A.13 of the MUTCD defines the median as ―the area between two

roadways of a divided highway measured from edge of traveled way to edge of traveled way.‖

Similarly, page 337 of the Green Book defines median width as, ―the dimension between the

edges of traveled way.‖ However, the Green Book goes on to specify that the median width

―includes the left shoulders, if any‖ which implies that the median width would also include any

median turn lanes. To the contrary, the MUTCD goes on to specify that, ―the median width

excludes turn lanes and might be different between intersections, interchanges, or on opposite

approaches of the same intersection.‖ Furthermore, Section 2A.23 of the MUTCD specifies a 30

foot median width (42 foot median width based on the Green Book definition assuming 12 foot

wide turn lanes) as a threshold for signing the near-side and far-side intersections as two separate

intersections, while page 456 of the Green Book states, ―where a median width of 25 feet or

more is provided, a passenger car making a turning or crossing maneuver will have space to stop

safely in the median area.‖ These inconsistencies create confusion for roadway designers and

traffic engineers; therefore, the Green Book and the MUTCD should coincide in these areas.

CONCLUSIONS

We recommend that more focus in the Green Book and the MUTCD regarding rural expressway

intersections be placed on strategies that address the most frequent type of intersection crash

(right-angle) and the most common factor contributing to these crashes (gap selection).

Although this paper identifies these and many other issues, most must be solved by others in the

future. For example, although thorough reviews of the Green Book and the MUTCD were

conducted with many resulting recommendations, modifications to the Green Book are made

through the AASHTO Technical Committee on Geometric Design and changes to the MUTCD

are made through the FHWA MUTCD Team and the National Committee on Uniform Traffic

Control Devices. The recommendations provided in this paper are meant for the consideration of

these groups and it is ultimately their responsibility to modify the contents of those manuals.

Furthermore, the safety effectiveness of the rural expressway intersection treatments examined in

Hochstein et al. 12

the case studies can only be determined if STAs are willing to deploy and rigorously evaluate

them. Therefore, while the recommendations are specific, others must implement them to

positively impact rural expressway intersection design and safety.

FUTURE RESEARCH NEEDS

The case studies revealed that there are promising safety treatment options for TWSC rural

expressway intersections (J-turn intersections, offset T-intersections, median acceleration lanes,

offset turn lanes, enhanced guide signing, and dynamic intersection warning systems) which can

help to avoid signalization and grade separation. These case studies also help to begin to

understand the safety improvement potential of these countermeasures and set the stage for the

development of a richer set of design options as shown in Figure 1B. However, it is believed

that experimentation with these innovative safety strategies is being hampered by the lack of

substantial proof that they improve safety without creating other operational issues. For these

innovative intersection designs, the development of a data collection protocol is recommended.

A statistically sufficient sample should be built, tested, and monitored to perform valid

evaluations. With solid evidence of safety improvement associated with these design

alternatives, more STAs may be willing to support their implementation. In addition to

determining their safety effects, more research is also necessary to determine the conditions

under which each treatment should be considered and under which each would be expected to

fail in terms of safety and/or operations.

ACKNOWLEDGMENTS

The study resulting in this publication was conducted as part of National Cooperative Highway

Research Program (NCHRP) Project 15-30, soon to be published as NCHRP Report 650 (8).

The NCHRP project panel was chaired by Tom Welch of the Iowa DOT. Other panel members

included Don Arkle – Alabama DOT, Drew Boyce – Delaware DOT, Rene Garcia – Texas DOT,

James Young – Ohio DOT, Michael Hurtt – Clough Harbour & Associates LLP, Dr. James

Gattis – University of Arkansas Fayetteville, Dr. Karl Zimmerman – Texas A&M University,

Gregory Davis – FHWA, and Richard Cunard – TRB. The project was managed by Ray Derr,

NCHRP Senior Program Officer.

During the preparation of this paper, Dr. Tom Maze passed away. Tom was a dedicated

transportation researcher/educator/mentor, a valued colleague, and a dear friend. This paper is

dedicated to his memory.

Hochstein et al. 13

REFERENCES

1 Maze, T.H., N.R. Hawkins, and G. Burchett. Rural Expressway Intersection Synthesis of

Practice and Crash Analysis: Final Report. Center for Transportation Research and

Education, Iowa State University, Ames, Iowa, October 2004.

http://www.ctre.iastate.edu/reports/expressway.pdf. (Accessed July 30, 2009).

2 Nebraska Department of Roads Highway Safety Division. Accident Experience of Rural

Highways: Two-Lane versus Four-Lane Expressways. Unpublished. Nebraska Department

of Roads, Lincoln, NE, February 2000.

3 Souleyrette, R.R., and T. Knox. Safety Effectiveness of High-Speed Expressway Signals.

Center for Transportation Research and Education, Iowa State University, Ames, Iowa,

August 2005. http://www.ctre.iastate.edu/reports/expressway_signals.pdf. (Accessed July

31, 2009).

4 Preston, H., R. Storm, M. Donath, and C. Shankwitz. Review of Minnesota’s Rural

Intersection Crashes: Methodology for Identifying Intersections for Intersection Decision

Support (IDS), Report #1 in the Series: Developing Intersection Decision Support Solutions.

CH2M Hill, University of Minnesota, Minnesota Department of Transportation, St. Paul,

MN, May 2004. http://www.lrrb.org/pdf/200431.pdf. (Accessed July 31, 2009).

5 Burchett, G.D., and T.H. Maze. ―Rural Expressway Intersection Characteristics as Factors in

Reducing Safety Performance.‖ In Transportation Research Record: Journal of the

Transportation Research Board, No. 1953, Transportation Research Board of the National

Academies, Washington, D.C., 2006, pp. 71-80.

6 American Association of State Highway and Transportation Officials. A Policy on Geometric

Design of Highways and Streets, Fifth Edition. AASHTO, Washington, D.C., 2004.

7 Federal Highway Administration. Manual on Uniform Traffic Control Devices for Streets

and Highways, 2003 Edition with Revisions Number 1 and 2 Incorporated. U.S. Department

of Transportation, Washington, D.C., December 2007.

http://mutcd.fhwa.dot.gov/kno_2003r1r2.htm. (Accessed July 30, 2009).

8 Maze, T., J.L. Hochstein, R.R. Souleyrette, H. Preston, and R. Storm. NCHRP 650: Median

Intersection Design for Rural High-Speed Divided Highways. Transportation Research Board

of the National Academies, National Research Council, Washington, D.C., (In publication).

9 Bonneson, J.A., P.T. McCoy, and J.E. Truby, Jr., ―Safety Improvements at Intersections on

Rural Expressways: A Survey of State Departments of Transportation.‖ In Transportation

Research Record: Journal of the Transportation Research Board, No. 1385, Transportation

Research Board of the National Academies, Washington, D.C., 1993, pp. 41-47.

Hochstein et al. 14

10 Hauer, E. Observational Before-After Studies in Road Safety: Estimating the Effect of

Highway and Traffic Engineering Measures on Road Safety. Elsevier Science, Inc.,

Kidlington, Oxford, UK, 1997.

11 Neuman, T.R., R. Pfefer, K.L. Slack, K.K. Hardy, D.W. Harwood, I.B. Potts, D.J. Torbic,

and E.R.K. Rabbani. NCHRP Report 500: Guidance for Implementation of the AASHTO

Strategic Highway Safety Plan, Volume 5: A Guide for Addressing Unsignalized Intersection

Collisions. Transportation Research Board of the National Academies, Washington, D.C.,

2003. http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_500v5.pdf. (Accessed July 30,

2009).

12 Leisch, J.P. Institute of Transportation Engineers Freeway and Interchange Geometric

Design Handbook. ITE, Washington, D.C., 2005.

13 Illinois Department of Transportation, Bureau of Design & Environment Manual – 2002

Edition, Springfield, IL (December 2002).

http://www.dot.state.il.us/desenv/BDE%20Manual/BDE/pdf/chap37.pdf (Accessed Nov. 12,

2009).

14 Missouri Department of Transportation Engineering Policy Group. ―Rural Expressway

Median Openings.‖ MoDOT Technical Bulletin, No. 1, May 2006.

http://www.modot.org/business/documents/TechnicalBulletinNo.1May06.pdf. (Accessed

July 31, 2009).

15 Staplin, L., K. Lococo, S. Byington, and D. Harkey. Guidelines and Recommendations to

Accommodate Older Drivers and Pedestrians. Report No. FHWA-RD-01-051. Federal

Highway Administration, McLean, VA, May 2001.

http://www.tfhrc.gov/humanfac/01105/cover.htm#toc. (Accessed March 5, 2010).

16 McCoy, P.T., U.R. Navarro, and W.E. Witt. ―Guidelines for Offsetting Opposing Left-Turn

Lanes on Four-Lane Divided Roadways.‖ In Transportation Research Record: Journal of

the Transportation Research Board, No. 1356, Transportation Research Board of the

National Academies, Washington, D.C., 1992, pp. 28-36.

Hochstein et al. 15

LIST OF TABLES

TABLE 1 Green Book Expressway Design Guidance Index

TABLE 2 MUTCD Expressway Intersection Signing, Marking, & Control Index

TABLE 3 Rural Expressway Intersection Safety Treatments

TABLE 4 Recommended Revisions to the AASHTO Green Book (6)

TABLE 5 Recommended Revisions to the MUTCD (7)

LIST OF FIGURES

FIGURE 1 Traditional & updated TWSC expressway intersection countermeasure paths.

FIGURE 2 Examples of enhanced at-grade expressway intersection guide signage.

Hochstein et al. 16

TABLE 1 Green Book Expressway Design Guidance Index

TOPIC CHAPTER PAGES

Ultimate Development of Divided Arterials 7 450 – 452

Access Management 7 466 – 467

Frontage Roads 4 339 – 344 7 464 – 465, 467 9 725 – 728

Right-of-Way (ROW) 7 449 – 452, 462 – 465 Design Speed 7 444

Design Traffic Volume/ Level of Service 7 444

Alignment (Vertical & Horizontal)

7 445 – 446, 457 – 458 9 582

Superelevation 7 446, 459 – 462 Number of Lanes 7 446, 454

Lane & Shoulder Widths 7 448, 455 – 456, 462 – 463 Cross Slope 7 446 – 447, 455, 459 – 462

Median Design (Width/Type/Opening Length/

End Treatment)

4 337 – 339 7 454 – 457, 465 – 466

9 566, 621 – 625, 627, 689 – 704, 709 – 713, 716 – 723

Signalization 7 466

Intersection Sight Distance 7 445 9 661 – 667, 674 – 675

Left-Turn Lanes/Paths 7 454, 456, 466 9 682, 685, 688 – 725

Design to Discourage Wrong-Way Entry

7 457, 466 9 679 – 682

Rural Freeways 8 508 – 512 Four-Legged Intersections 9 568 – 572

Offset Left-Turn Lanes 9 674 – 675, 723 – 724 Right-Turn Lanes 9 688 – 689, 713 – 716 Intersection Skew 9 700 – 704

Indirect Left-Turns & U-Turns 9 705 – 712 Intersection Lighting 9 729

One-Quadrant Interchanges 10 743 – 744, 747, 776 – 777 Interchange Warrants 10 745 – 749

Auxiliary/Speed-Change Lanes 10 814 – 818, 844 – 856

Hochstein et al. 17

TABLE 2 MUTCD Expressway Intersection Signing, Marking, & Control Index

TOPIC SECTION FIGURES/TABLES Definitions for Expressway & Median 1A.13, 2A.01

Sign Dimensions 2A.12 Overhead Sign Installations 2A.17

Sign Mounting Height 2A.18 Figure 2A-1 Median Opening Treatments for Divided Highways

with Wide Medians 2A.23

Size of Regulatory Signs 2B.03 Table 2B-1 YIELD Sign Applications 2B.09 Turn Prohibition Signs 2B.19 Figure 2B-3

Mandatory Movement Lane Control Signs 2B.21 Figure 2B-4 Keep Right Signs 2B.33 Figure 2B-8

DO NOT ENTER Sign WRONG WAY Sign

2B.34 2B.35

Figure 2B-9 Figure 2B-10

ONE WAY Signs DIVIDED HIGHWAY CROSSING Signs

2B.37 2B.38

Figure 2B-11 Figure 2B-12 Figure 2B-13 Figure 2B-14 Figure 2B-15

KEEP OFF MEDIAN Signs 2B.47 Figure 2B-20

Size of Warning Signs 2C.04 Table 2C-2 Table 2C-3

Divided Highway (Road) Sign 2C.18 Figure 2C-3 Divided Highway (Road) Ends Sign 2C.19 Figure 2C-3

Lane Ends Signs 2C.33 Figure 2C-6 Crossover Signs 2D.51 Figure 2D-12

Freeway and Expressway Guide Signing Principles 2E.02 Characteristics of Rural Signing 2E.07

Guide Sign and Lettering Size and Style 2E.13 – 2E.15 Table 2E-1 Table 2E-2

Lateral Offsets for Guide Signs 2E.23 Guide Sign Classification 2E.24

Route Signs & Trailblazer Assemblies 2E.25 Figure 2E-11 Guide Signs for Intersections At-Grade 2E.26

Delineator Application 3D.03 Studies & Factors for Justifying Traffic Control Signals 4C.01

Size, Number, and Location of Signal Faces 4D.15 Visibility, Shielding, and Positioning of Signal Faces 4D.17 Lateral Placement of Signal Supports and Cabinets 4D.19

Hochstein et al. 18

TABLE 3 Rural Expressway Intersection Safety Treatments

Category Subcategory Treatment

Conflict Point Management Techniques

Removal/Reduction Through Access

Control

1) Conversion of Entire Expressway Corridor to Freeway 2) Isolated Conversion to Grade Separation or Interchange 3) Close Low Minor Road Volume Intersections & Use Frontage Roads to Direct Traffic to Major Intersections 4) Close Median Crossovers (Right-In, Right-Out Access Only) 5) Convert Four-Legged Intersection into T-Intersection or Initially Construct T-Intersections instead of Four-Legged Intersections Offset T-Intersections

Use a “One-Quadrant Interchange” Design (if necessary)

Replacement of High-Risk Conflict

Points

1) J-Turn Intersections (Indirect Minor Road Crossing & Left-Turns) 2) Offset T-Intersections (Indirect Minor Road Crossing) 3) Jughandle Intersections (Indirect Left-Turns Off Expressway) 4) Other Indirect Left-Turn Treatments (Michigan Lefts) 5) Expressway Semi-Roundabout Intersection (ES-RI)

Relocation or Control

1) Provide Left/Right-Turn Lanes or Increase Their Length 2) Provide Free Right-Turn Ramps for Exiting Expressway Traffic 3) Minimize Median Opening Length 4) Signalization

Gap Selection

Aids

Vehicle Detection (Intersection Sight

Distance Enhancements)

1) Provide Clear Sight Triangles 2) Modify Horizontal/Vertical Alignments on Intersection Approaches 3) Realign Skewed Intersections to Reduce or Eliminate Skew 4) Move Minor Road Stop Bar as Close to Expressway as Possible 5) Provide Offset Right-Turn Lanes 6) Provide Offset Left-Turn Lanes

Judging Arrival Time

1) Intersection Decision Support (IDS) Technology or Other Dynamic Device to Communicate Availability & Size of Gaps 2) Roadside Markers/Poles (Static Markers at a Fixed Distance)

Merging/Crossing Aids

- - - - - - - - - - - - -

(Promoting Two-Stage Gap Selection)

1) Provide Left-Turn Median Acceleration Lanes (MALs) 2) Provide Right-Turn Acceleration Lanes 3) Expressway Speed Zoning/Enforcement Near Intersections 4) Widen Median to Provide for Adequate Vehicle Storage 5) Add Centerline, Yield/Stop Signs/Bars, and Other Signage (“Recheck Cross Traffic Before Proceeding” or “Look” signs) in the Median 6) Extend Left Edge Lines of Expressway Across Median Opening 7) Public Education Campaign Teaching Two-Stage Gap Selection

Intersection Recognition

Devices

Intersection Treatments

1) Provide Overhead Control Beacon Reinforcing Two-Way Stop Control 2) Provide Intersection Lighting

All Approaches 1) Enhanced (Overhead/Larger/Flashing) Intersection Approach Signage

Expressway Approaches

1) Provide Enhanced Freeway-Style Intersection Guide Signs 2) Provide Dynamic “Watch For Entering Traffic When Flashing” Signs or Other Activated Advance Intersection Warning Systems 3) Use a Variable Median Width (Wider in Intersection Vicinity) 4) Change Median Type in Vicinity of Intersection

Minor Road Approaches

1) Use “Stop-Ahead” Pavement Marking & In-Lane Rumble Strips 2) Provide a Stop Bar (or a Wider One) 3) Provide Divisional/Splitter Island at Mouth of Intersection 4) Provide Signage/Marking for Prevention of Wrong-Way Entry

Note: Highlighted treatments were examined in NCHRP 650 (8) case studies.

Hochstein et al. 19

TABLE 4 Recommended Revisions to the AASHTO Green Book (6)

CATEGORY IDENTIFIED ISSUE POTENTIAL REVISIONS

Organizational Changes

Spread of expressway & expressway intersection design guidance throughout Chapters

4, 7, 8, 9, and 10.

Reorganize all expressway design guidance into a single comprehensive chapter.

Include all rural expressway intersection design guidance within a separate section of Chapter 9. Create a companion “Expressway Intersection

Geometric Design Handbook”.

Philosophical Changes

Lack of planning for expressway intersection safety.

Include a discussion regarding the strategic placement of intersections during expressway

corridor planning. Develop & include proactive guidelines based on safety considerations which define when to start

planning for or constructing the next level of intersection design.

Design Guidance Updates

Current design guidance for offset left-turn lanes, jughandle intersections, & median U-turn

intersections is limited.

The design guidance for these three alternative intersection designs should be updated &

expanded. More details can be found in the NCHRP 650 (8) case studies.

Page 709 currently discourages the use of J-Turn Intersections on high-speed expressways.

Statement on page 709 regarding J-Turn Intersections should be revised as J-Turns have successfully been used on rural expressways.

No discussion of minor road driver gap selection issues and

few design solutions to this problem are currently

presented.

Design guidance for median intersection design options which address minor road driver gap

selection issues (i.e., J-turn intersection, offset T-intersection, offset right-turn lanes, median

acceleration lanes, etc.) should be added or at least discussed.

Hochstein et al. 20

TABLE 5 Recommended Revisions to the MUTCD (7)

CATEGORY IDENTIFIED ISSUE POTENTIAL REVISION

Assistance for Minor Road

Drivers

Current edition does not address the need for or the application of devices to assist minor road drivers with gap

selection.

Identify and describe the use of traffic control devices, signs, and/or pavement markings which would assist minor road

drivers with judging and selecting safe gaps (i.e., Intersection Decision Support, static

roadside markers, median delineation, median signage, etc).

Assistance for Expressway

Drivers

There is no existing guidance for differentiating the relative probability of conflict at one intersection vs. another.

Include language which supports the use of freeway-style advance guide signs,

diagrammatic signs, and dynamic warning devices on expressway approaches to at-grade intersections with higher crash risk (i.e., higher volume minor roads, skewed intersections, horizontal/vertical curves on

the mainline, etc.)

Existing guidance for expressway intersection guide signing directs the

user to use the same signage specified for intersections on

conventional roads. No examples of diagrammatic signing for at-grade expressway intersections.

Such examples (Figure 2B) should be included in Section 2E.19 or 2E.26.

Figure Modifications

MUTCD FIGURE 2B-10 Add double yellow centerline and stop bars within the median.

MUTCD FIGURE 2B-13 Add median width dimensioning. MUTCD FIRGURE 2B-14 Include option for median Yield signs/bars.

MUTCD FIGURE 2B-15

Add median width dimensioning, include option for median Yield signs/bars, show

positively offset left-turn lanes, and include “offset” in the figure title.

Figures 2B-10 & 2B-13 both show regulatory signing plans for

intersections with medians ≥ 30 feet and conventional left-turn lanes.

Create a single standard regulatory signing and pavement marking plan for each

combination of median width and left-turn lane type (4 conditions).

Figure Additions

No figure for medians ≥ 30 feet and offset left-turn lanes.

Add signing and marking guidance similar to that recommended by Staplin et al. (15)

for this condition.

No figure showing WRONG WAY signing for medians < 30 feet.

Add a figure showing WRONG WAY signing for this condition or remove median

width qualification from Figure 2B-10.

No figure showing standard warning and/or guide signing for TWSC rural

expressway intersections.

Add a figure showing warning and guide signing for typical TWSC rural expressway intersections as well as enhanced warning and guide signing for higher volume/critical

intersections.

No figures showing standard signing and marking plans for non-traditional

expressway intersection designs.

Add such figures for J-Turn Intersections, Offset T-Intersections, Jughandles, Median

Acceleration Lanes, & Offset Right-Turn Lanes.

Technical Modifications

(Inconsistencies)

MUTCD definition of median width inconsistent with AASHTO Green

Book (6) definition.

Redefine median width to match AASHTO Green Book (6) definition (i.e., include median turn lanes in median width).

There is no clear reason given why a 30-foot median width (MUTCD

definition) is selected as the threshold for different one-way signing plans.

If 30 feet is selected due to vehicle storage requirements, this should be explained

since this differs from the 25-foot minimum stated in the Green Book (p. 456).

Hochstein et al. 21

FIGURE 1 Traditional & updated TWSC expressway intersection countermeasure paths.

Hochstein et al. 22

FIGURE 2 Examples of enhanced at-grade expressway intersection guide signage.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E.

Sample of Work – Exhibit C

SAFETY EFFECTIVENESS OF STOP CONTROL AT ULTRA-LOW VOLUME UNPAVED INTERSECTIONSCorresponding Author:

Reginald R. SouleyretteDepartment of Civil, Construction and Environmental Engineering and Center for Transportation Research & Educationreg@iastate.edu

Ryan J. TengesGraduate Student/Research AssistantCenter for Transportation Research & Educationryant@iastate.edu

Thomas McDonaldCenter for Transportation Research & Educationtmcdonal@iastate.edu

T.H. Maze Department of Civil, Construction and Environmental Engineering and Center for Transportation Research & Educationtmaze@iastate.edu

Alicia CarriquiryDepartment of Statisticsalicia@iastate.edu

Iowa State University2901 S. Loop Drive, Suite 3100Ames IA 50010(515) 294-8103 (515) 294-0467 (fax)

Submitted: July 29, 2005Word Count: 3744 words + 11 tables and figures = 6,494

Souleyrette, Tenges, McDonald, Maze, Carriquiry 1

SAFETY EFFECTIVENESS OF STOP CONTROL AT ULTRA-LOW VOLUME UNPAVED INTERSECTIONSReginald R. Souleyrette, Ryan J. Tenges, T. H. Maze and Alicia Carriquiry

ABSTRACT

Establishment of the proper level of traffic control on low volume rural roads can be problematic for local agencies. This paper presents the results of a study of 10 years of crash data for over 6000 rural, unpaved intersections in Iowa comparing stop to no-control. Crash models were developed using logistic regression and hierarchical Poisson estimation. For ultra-low volume intersections, under 150 vehicles per day, results indicate no statistical difference in the safety performance of each level of control. The effect of excessive use of control on safety performance was also tested for rural and urban applications, generally indicating no detrimental effect.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 2

INTRODUCTIONEstablishment of the proper level of traffic control on low volume rural roads can be problematic for local agencies. Intersections in particular present challenges for engineers in selecting appropriate control for varying situations. The Manual on Uniform Traffic Control Devices (1), MUTCD, presents limited guidance for STOP and YIELD signs applications in Part 5 – Traffic Control Devices for Low Volume Roads. Part 2 of the MUTCD discourages overuse of regulatory signs and lists general applications for installation of STOP and YIELD signs. Excessive use of STOP signs in particular is thought to encourage disrespect and violations by drivers, add operational costs to agency budgets, and expose agencies to potential liability for deficient maintenance. However, no published guidelines for removal of unneeded two-way stopcontrol apparently exist and local agencies are reluctant to undertake this action even at ultra-lowvolume intersections (identified in this report as intersections with less than 150 daily entering vehicles, DEV).

This study had two primary objectives. First, the study was to assess the safety performance of STOP versus no control at ultra-low volume unpaved roads for a large data set (over 6000 intersections in Iowa and 10 years of data). The second objective was to developcriteria to assess the excessive use of stop control and analyze the effects of extensive versus lesser use of STOP signs. Legal implications were also studied, and guidance was developed for the safe removal of unneeded control. These are available in the project report but are not presented in this paper due to length limitations.

LITERATURE REVIEWWe reviewed applications for the installation of stop and yield control at intersections as contained in the MUTCD (1) and the Institute of Transportation Engineers (ITE) Traffic Control Devices Handbook (2). While providing basic guidance for the establishment of intersection control, neither document includes definitive recommendations for ultra-low volume roadwaysor any guidance for removal of unneeded control.

The most common criteria for establishing or increasing control at intersections are traffic volumes, sight distance, and crash history. However traffic volumes considered in many studies are much higher (approximately 2000-6000 DEV.) than commonly exist on local roads in rural Iowa. In addition, several studies found that the most frequent crash factor at these locations was not STOP sign violations, but failure to yield right of way from the stop position (3, 4, 5, and 6). Other research found that available sight distance at low volume intersections may have negligible effect on safety and operations (7 and 8). These studies concluded that major road traffic volume should be the most prevalent factor in determining level of control.

The FHWA conducted a study in 1981 to attempt to establish definitive criteria for the application of two-way STOP or YIELD at low volume intersections (8). After completing an analysis of variance, the researchers observed a significant increase in crash experience when the volume on the major roadway reached 2000 vehicles per day.

Based on AASHTO recommendations (9), most rural intersections in Iowa would require stop control at least part of the year due to crops. The MUTCD (1), however, recommends that if a full stop is not necessary at all times, consideration of less restrictive control should be given. Both AASHTO and ITE methods assume that drivers reduce speeds when approaching an uncontrolled intersection.

NCHRP Report 320 discusses the conversion of stop to yield control (3). The report found that converted intersections experienced an increase in crashes, the severity and distribution of crashes did not significantly change, and converted intersections had higher crash

Souleyrette, Tenges, McDonald, Maze, Carriquiry 3

rates than unchanged intersections. According to the study, candidates for conversion to yield control should have adequate sight distance, volume less than 1800 DEV, and less than three crashes in two years.

Finally, conflicting conclusions as to the safety effectiveness of stop control were evident in some research (10, 11).

SURVEY AND DATA COLLECTIONTo determine the scope of practice in Iowa, we chose to survey county engineers on practices and policies for the installation of traffic control at rural local road intersections. Information sought in the survey included type of control utilized, criteria employed for determining level of control, use of engineering studies, and adoption of formal policies for application of stopcontrol. Twenty-nine of Iowa’s ninety-nine counties responded to the survey.

Of the counties responding, five indicated no uncontrolled intersections in their jurisdictions, while eleven had more than 200 without control, all in unpaved locations. Three counties have no all-way stop intersections, but two have more than 100 all-way stop locations, all with at least one paved approach. The use of Yield signs is not common on local rural roadsand twelve counties have no Yield signs in use.

Crash history is the most popular determinant for stop control in the counties, followed by sight distance. The majority of responding counties employ an engineering study prior to installing STOP signs, but most have not adopted a formal policy for this application. We also found that the two most popular references used by county engineers in Iowa for engineering studies are the MUTCD and the guidelines used by the Iowa Department of Transportation (Iowa DOT).

In addition to the survey responses, nineteen counties furnished data describing the location of STOP and YIELD signs in their jurisdictions. From these data, it was possible to determine the location of all stop, yield, and uncontrolled intersections in these counties and maps were prepared to illustrate these control types. Following the selection of all unpaved study intersections, crash history was reviewed for a ten-year period. To better assess the effects of stop and yield control, only multi-vehicle crashes of specific types and only those occurring within 150 feet1 of the intersection were included. Daily entering vehicle volumes were compiled and Iowa DOT crash costs were used to assess severity.

These data indicated that, in general, stop controlled intersections exhibit lower totals for number of crashes, average crash rate, average severity, and average cost per crash than uncontrolled intersections. However, most crashes (~80%) on local rural roads in Iowa involve only single vehicles and were thus not included. Crash rates at both stop and uncontrolled unpaved intersections in Iowa are very low.

RURAL ANALYSISTo identify relationships within the data, a descriptive statistical analysis was conducted initially, considering 6,846 unpaved rural intersections. Fifty-six percent of these intersections were uncontrolled and approximately ninety-two percent of all study intersections had not recorded a crash over a ten year period. Two variables were considered: Daily entering vehicles and type of control. Maximum traffic for the study intersections included in this analysis was 200 DEV.

A crash type examination revealed that most crashes at intersections on ultra-low volume, unpaved rural roads are caused by driver failure to yield the right of way. At stop controlled

1 DOT criterion for intersection-related

Souleyrette, Tenges, McDonald, Maze, Carriquiry 4

locations, most of these crashes occurred after a driver had stopped but then proceeded to pull into the path of another vehicle. Ignoring or not seeing a STOP sign was not listed as a major crash cause. For both stop and uncontrolled intersections, vision obscured due to crops or other obstacles was not noted as a major contributory factor. Broadside/right angle was the primary crash type at both control types.

An initial analysis indicated that crashes and rate both increase as DEV increases. In addition, a difference in safety performance between stop and uncontrolled intersections was first noted around 70 DEV (See Figure 1). A traffic volumes above this point, stop controlled locations exhibit fewer crashes, while with lower DEV, little difference between types of controlcan be observed. Average severity per crash was similar for all traffic levels, regardless of control type. Considering only safety cost, it is at this divergent point that consideration should first be given to control. However, total costs would of course include crash, maintenance, and delay costs.

FIGURE 1 Average number of crashes per intersection on a countywide basis.

An approximate cost analysis was completed assuming a delay of seven seconds per vehicle for stop control (verified in field trials), vehicle operating cost of $15.00/hr., and annual

Souleyrette, Tenges, McDonald, Maze, Carriquiry 5

maintenance/replacement cost of fifty dollars per intersection. Factoring in total costs, the performance of stop and no control is therefore essentially the same below about 150 DEV.

Regression AnalysisFollowing the initial analysis, more in-depth study was undertaken. Due to the small range of variance in the number of crashes recorded at these intersections, a logistic regression was completed to establish the relationship between type of control, DEV, and the probability of a crash occurrence over a ten year period. Available sight distance was not included in the regression. In this analysis, safety performance of stop and uncontrolled diverges at a point near 100 DEV (see Figure 2.). A ninety-five percent confidence interval for this divergent point is between 66 and 140 DEV. Above this traffic volume level, the probability of at least one crash in a ten year period increases more dramatically for uncontrolled intersections than stop controlled. At lower volumes, little difference in safety performance was noted.

FIGURE 2 Probability of one or more crashes in ten years.

Effect of Driver AgeImpacts of driver age on crash statistics were examined considering specifically drivers 65 years of age and older as well as those 19 years old and younger. Regardless of control type, it was found that drivers in the younger group are slightly overrepresented in these intersection crashes. Older drivers, by contrast, are involved in crashes at these ultra-low volume intersections at a

Souleyrette, Tenges, McDonald, Maze, Carriquiry 6

much lower rate than the overall statewide average for all crashes for that age group. From this, it was concluded that older drivers either avoid these locations or use appropriate care when passing through the intersections.

Quantifying Excessive UseAs part of this study, the suggestion that excessive use of STOP signs might indirectly contribute to an increased number of crashes in a jurisdiction was tested. To do this, several individual analyses were undertaken. First, the percentage of stop controlled intersections for each county was determined and plotted against average crash rate (See Figure 3). This plot indicated that crash rates seem to decline as the level of control is increased. Furthermore, it was found that this observation for unpaved intersection crashes was apparently unaffected by the overall crash rate in a specific county. When the average crash rate was adjusted for DEV, similar results were obtained, as percent control increases, crash rates appear to decline.

FIGURE 3 Safety performance based on the percentage of stop controlled intersections per county.

As a STOP sign placed in response to sight distance limitations is not considered excessive, and sight distance was not available for study area intersections, a terrain factor was developed to act as a surrogate for the expected fraction of stop control required for sight distance. United States Geographical Services, USGS, maps were used to determine terrain factors for each study county considering topography and land cover. Combining minimum volume thresholds with various terrain factor formulations (provided for sensitivity analysis), estimated numbers of “justified” stop controlled intersections were calculated. When the fraction of excess STOP signs was plotted against crash rate, again it was found that adding

Souleyrette, Tenges, McDonald, Maze, Carriquiry 7

STOP signs appeared to reduce crash rates. See Figure 4 produced using a volume threshold of 100 (the approximate level at which stop control appears to provide some safety benefit) and one of the terrain factor formulations (set 3). A field survey of three of the study area counties indicated that the terrain factor computed “justified fraction” matched two counties well (Adams and Boone), but failed to accurately estimate the fraction in the third County (Madison).

FIGURE 4 Percentage of excess stop controlled intersections, adjusted for terrain and volume threshold.

An Alternative Excessive Use FormulationThe effect of excess use of STOP signs on safety performance was investigated further using an “average” county as the standard for the number of stop controlled intersections per county. Cherokee County, with a relatively low number of stop controlled intersections (93), average topography, traffic volumes, and land cover was selected as “average”. A ratio based on Cherokee County stop control was calculated for all study counties and plotted against average observed crash rates (See Figure 5). This analysis method also indicated a general decrease in crashes with the increasing use of STOP signs.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 8

FIGURE 5 Crash performance vs. “Cherokee County” excess use factor.

Safety performance in counties with more than twice2 the number of stop controlled intersections as compared to Cherokee County was compared to performance in other counties (See Figure 6). When plotted, trends for the two groups cross at approximately 125 daily entering vehicles, indicating that above that volume, the excessive use of STOP signs may be detrimental to safety performance. This finding is contradictory to our earlier findings.

2 Subjectively determined to explore the potential explanatory power of the factor.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 9

FIGURE 6 Effect of excessive use based on Cherokee County factor.

URBAN APPLICATIONTo study the effects of intersection control in an urban area, an in-depth review of non-signalized intersections was undertaken in the City of Ames, using video logging. Five levels of control were compared for a ten-year crash history. Figure 7 illustrates the crash performance of each type of control. The best safety performance was observed at all-way stop control (see Table 1). Yield control exhibited the highest crash rate followed by no control, traffic signal, and two-way stop, respectively (the rates for the latter three control types were very similar).

Table 1 Summary for City of Ames.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 10

FIGURE 7 Intersection performance of Ames intersections.

Statistical AssessmentWe fitted a hierarchical Poisson model to the Ames crash data. The model states that crashfrequencies at an intersection are distributed as Poisson variables with mean λ * DEV, where here λ is defined as crash frequency divided by DEV. The log of lambda is then modeled as a function of the type of control and a random error. Because very few Yield-controlled intersections were available in this dataset, we grouped the Yield-controlled and the intersections with no control. Dummy variables were defined for the four types of control, and the no control group was used as the reference. The error in the second level of the model was assumed to be normal (implying that log (λ) is also normal).

Estimates of model parameters were obtained using a Bayesian approach (12). The regression coefficients associated to control types were assigned non-informative normal prior distributions with zero mean and very large variance, indicating that a priori, we do not assume any differences in crash rates due to control type. The prior distribution for the variance of the error was an inverted gamma distribution with mean equal to one and very large variance, again to reflect prior ignorance about the distribution of the error. A priori, the regression coefficients and the variance component were assumed to be independent, and the joint prior distribution was semi-conjugate to the sampling distribution.

We fitted the model using WinBUGS and Markov chain Monte Carlo methods. We obtained posterior distributions of expected crash frequency at each intersection (where frequency is defined as the expected number of crashes at the intersection given its DEV), expected crash rate at each intersection, defined here as the number of crashes per million

Souleyrette, Tenges, McDonald, Maze, Carriquiry 11

entering vehicles (MEV), and expected average crash rate at intersections of each of the different types.

Posterior distributions are summarized by their mean, standard deviation, and 2.5th, 50th

and 97.5th percentile. A central 95% posterior credible set is given by the set bounded by the 2.5th

and the 97.5th posterior percentiles. Table 2 shows the posterior distributions of expected crash rates (number of crashes per MEV) at intersections with each of the four control types. For example, the likely values of crash rate for intersections with a two-way STOP sign are 0.27 to 0.30. If the credible sets for two types of intersections do not overlap, we conclude that there are significant differences between them. For example, signal-controlled intersections have significantly higher crash rates than all others. Two-way stop controlled intersections have significantly lower crash rates than all others. There is no difference in crash rates between the all-way and the no-control intersections. The plots in Figure 8 show the posterior distributions of crash rates for the various intersection types.

TABLE 2 Expected Crash Rates

FIGURE 8 Crash rate distributions based on control type.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 12

Effect of Excessive UseTo investigate the possible effect of excessive stop sign use, neighborhood crash rates were compared to city-wide averages. Figure 9 plots overall and stop controlled crash rates for each neighborhood versus percent control. For this limited urban application, increased use of stop control would seem to have a positive impact on safety performance (note that the x-axis indicated uncontrolled portion)

FIGURE 9 Safety performance of Ames neighborhoods.

CONCLUSIONS AND RECOMMENDATIONSThis research has found that ultra-low volume, unpaved rural intersections experience no adverse impact to safety performance due to type of control. Agencies may have erected Stop signs inthese locations in the past and may desire to remove perceived unneeded control.

Conclusions drawn from this research include:- In general, ultra-low volume, rural, unpaved intersections exhibit crash rates much

lower than those experienced on local rural roads in general- The most prominent crash type at study intersections was failure to yield right of way,

regardless of control type- Additional STOP sign use at these ultra-low volume intersections did not appear to

adversely affect safety performance- Above approximately 150 DEV, uncontrolled intersections exhibit increasingly

higher crash rates than stop controlled- For both stop and uncontrolled ultra-low volume rural unpaved intersections, older

drivers have less crashes than would be expected

Souleyrette, Tenges, McDonald, Maze, Carriquiry 13

- For intersections with DEV less than approximately 150, type of control has negligible effect on the safety performance of ultra-low volume unpaved rural intersections

- restricted sight distance is not a major contributing crash factor at ultra-low volume intersections, regardless of control type

- In urban areas, excessive use of stop control may adversely affect safety performance, but more research is needed to verify.

- Several sources of references for conversion of all-way to two-way stop control are available, but guidelines for removal of two-way STOP signs have not been published.

- The effect of excessive use of stop control on safety performance of stop controlled intersections is statistically inconclusive

- If proper techniques and criteria are followed, it appears that agencies could remove or convert stop controlled low volume intersections without exposure to liability.

Recommended procedures for removal or conversion of 2-way Stop control from low volume rural locations include (1) establishment of a formal policy, (2) consultation with agency legal counsel and traffic control experts, (3) review of MUTCD applications for Stop and Yield signs (4) appropriate public notice, (5) documentation and follow-up review.

If removal or conversion of unneeded STOP signs is desired, agencies should consider more extensive use of YIELD signs at locations where visibility is hampered for part of the year due to crops. Additional study of low volume intersection control in urban areas is needed and a long term (3-5 years) investigation of actual removal of two-way stop control and/or conversion to yield control would be beneficial.

ACKNOWLEDGMENTSThe authors gratefully acknowledge the support of the Iowa Highway Research Board which has not yet given final approval of the full project report. We also appreciate the support of the Midwest Transportation Consortium. Responsibility for the facts and opinions presented rest solely on the authors.

REFERENCES1. U.S. Department of Transportation Federal Highway Administration. Manual on Uniform

Traffic Control Devices. U.S. Department of Transportation Federal Highway Administration, Washington, D.C., 2001.

2. Institute of Transportation Engineers. Traffic Control Devices Handbook. Institute of Transportation Engineers, Washington D.C., 2001.

3. McGee, H.W., and Blankenship, M.R. Guidelines for Converting Stop to Yield Control at Intersections. NCHRP Report 320, TRB, National Research Council, Washington, D.C., 1989.

4. Stokes, Robert. Analysis of Rural Intersection Accidents Caused by STOP sign Violation and Failure to Yield the Right-of-Way. Kansas State University, Manhattan, KS, Report No. K-TRAN: KSU-98-6, September 2000.

5. Stokes, Robert. Effectiveness of Two-way Stop Control at Low-Volume Rural Intersections. Kansas State University, Manhattan, KS, Report No. K-TRAN: KSU-99-5, March 2004.

Souleyrette, Tenges, McDonald, Maze, Carriquiry 14

6. Preston, H. and Storm, R. Reducing Crashes at Rural Thru-STOP Controlled Intersections. CH2M Hill, Eagan, MN, 2003.

7. Mounce, J.M. Driver Compliance with Stop-Sign Control at Low-Volume Intersections. In Transportation Research Record 808, TRB, National Research Council, Washington, D.C., 1981, pp. 30-37.

8. Stockton, W.R., Brackett, R.Q., and Mounce, J.M. Stop, Yield, and No Control at Intersections. U.S. Department of Transportation Federal Highway Administration. FHWA/RD-81/084. June 1981.

9. American Association of State Highway Transportation Officials. A Policy on Geometric Design of Highways and Streets. American Association of State Highway Transportation Officials, Washington, D.C., 2001.

10. Lum, H. and Stockton, W. STOP sign Versus YIELD sign. In Transportation Research Record 881, TRB, National Research Council, Washington, D.C., 1982, pp. 29-33.

11. Bretherton, W.M., Jr. Multi-way Stops: The Research Shows the MUTCD is Correct! In ITE Annual Meeting Compendium, 1999, TRB, National Research Council, Washington, D.C., 1999.

12. Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B. 2004. Bayesian Data Analysis. 2nd ed. Chapman & Hall/CRC, Boca Raton, Florida, 668 pp.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E.

Sample of Work – Exhibit D

Computer-Aided Civil and Infrastructure Engineering 24 (2009) 1–19

Investigating the Use of 3D Graphics, Haptics(Touch), and Sound for Highway Location Planning

Chris HardingHuman-Computer Interaction Program, Virtual Reality Applications Center (VRAC),

Iowa State University, Ames, IA, USA

&

Reginald R. Souleyrette∗

Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA, USA

Abstract: Planning of transportation infrastructure re-quires analyzing combinations of many different typesof geospatial information (maps). Conventional Geo-graphic Information Systems (GIS) or Computer AidedDesign systems limit the planner’s ability to perceive andeffectively use multiple data layers together. To improvethe planner’s ability to interact with multiple layers ofdisparate spatial information, we present a novel com-puter system, which combines vision with haptics (touch)and sound. In this new form of Multi-Sensory Informa-tion System (MSIS), visual information is augmented bya three-dimensional haptic device (PHANToM) and bysound (sonification). In a recent study, we investigatedhow engineering students used this multi-sensory GIS forplanning the location (the alignment) of a new road. Theresults indicate that certain forms of vision, haptics, andaudio were used preferentially to represent certain typesof spatial data. A generalization of such a multi-sensoryapproach could provide researchers with the basis forfurther development and, eventually, the augmentationof established procedures with the MSIS in highway lo-cation planning and related areas.

∗To whom correspondence should be addressed. E-mail: reg@iastate.edu.

1 INTRODUCTION

In this article, we present preliminary evidence for theutility of using combinations of vision, touch, and sound(multi-sensory) systems in an area of civil engineering.Although our contribution draws from previous workfrom many different disciplines (such as GIS, percep-tional psychology, human-computer-interaction, com-puter science, physics, and music), its novelty lies in theway it combines this multitude of roots and, for the firsttime, applies it to the specific technical field of highwaylocation planning. At the center of our work is a lim-ited, albeit practical, test of multi-sensory highway loca-tion planning. As no existing software (commercial orresearch) exists that allows an engineer to interact withgeospatial data via an integration of sight, sound, andtouch, we developed our own software application thatuses specific, touch-enabling hardware. Furthermore,we design new ways of expressing several common GISdata types via sound and via touch (in addition to vi-sual) and integrate these visual/sound/touch expressionsof GIS data into a workflow that is flexible enough to betested for highway location planning. By creating andtesting this multi-sensory system and by documentinghow a number of users approached a typical planningcase, we suggest a potential shift in the way engineersand planners may, in the future, interact with geospatialdata in the workplace.

C© 2009 Computer-Aided Civil and Infrastructure Engineering.DOI: 10.1111/j.1467-8667.2008.00591.x

2 Harding & Souleyrette

We propose going beyond traditional visual-only sys-tems by using combinations of vision, touch, and sound.For our initial investigation into the use of such multi-sensory systems in the area of civil engineering, we havefocused on planning the preliminary alignment (the ini-tial road corridor) for rural highways. We hope the gen-eralization of such a multi-sensory approach may pro-vide the planning and engineering community at largewith a novel framework that may later be used to reeval-uate and augment established planning and engineer-ing procedures. Such a multi-sensory system would useemerging “virtual reality” technologies to empower itsusers and to enhance their cognitive abilities for per-ceiving spatial data in new and different ways. Com-pared to traditional mouse/keyboard driven applica-tions, which still impose a usability barrier betweenusers and spatial data, these multi-sensory applicationsmay better support direct user interaction with spatialdata, let the users “express” their intentions in real time,and establish a tightly coupled sensory loop between theusers and their data. Such a holistic interaction with spa-tial data may dramatically enhance a user’s ability toapply expert knowledge and past experiences to spatialplanning tasks such as defining initial road alignments.

This research is inherently multi-disciplinary andinvolves aspects of civil engineering as well as three-dimensional (3D) computer graphics, cartography, hap-tics, sonification, virtual reality, human-computer inter-action, and psychology. We realize that there are stillmany speculative elements in this approach; however,we believe it is important to inform the engineeringcommunity about current technical developments to ini-tiate a dialog about the practical aspects (feasibility) ofsuch a next generation system. We hope that the mate-rial presented here will stimulate thinking outside thetraditional boundaries of the discipline and encouragesimilar multi-disciplinary projects.

Section 2 (Background) puts this research into con-text with some of these aspects (disciplines) and Section3 (Methods: Technology Used in Our System) presentsthe technology used for this novel system. Section 4(Data Used in the User Study of the Road Planning Sys-tem) shows how different types of geospatial data maybe represented visually and via touch and sound, andSection 5 (A User Study of a Multi-Sensory Road Plan-ning System) reports on the methods and results of ausability study by 12 senior level civil engineering stu-dents. Section 6 provides an outlook on future develop-ments of the system.

2 BACKGROUND

2.1 Geographic information systems and highwaylocation planning

Geographic Information Systems (GIS) (Spear andLaksmanan, 1998; Mark, 2003; Sarasua et al., 1999)

provide tools for storing, analyzing, visualizing, and ma-nipulating different forms of electronic geospatial data(e.g., digital elevation models, satellite images, roaddata, point samples), which are stored as layers (Fig-ure 1) and are “draped” over parts of the Earth’ssurface.

A very simplistic example of so-called vector data isshown in Figure 2. The polygons represent types of landuse (wooded area, open spaces, lake, and towns), thelines represent rivers and roads.

Geographic Information Systems are commonly usedfor planning new infrastructure such as roads, railroads,pipelines, or power lines. Increasingly, GIS incorporatefunctionality typically thought of as Computer AidedDesign (CAD) functionality (and vice versa), and ouruse of the term GIS pertains to the mixed GIS/CADsystems now commonly used in engineering. A roadplanning project, on which we focus here, uses a com-bination of thematic layers of geospatial data, such asexisting roads, urban structures (such as cities), the ter-rain’s elevation (digital elevation model or DEM), thesoil’s engineering properties, and environmentally con-strained areas (like wetlands). An example of com-bined, overlapping data layers used in planning a high-way connection in a rural area is shown in Figure 3.Note: Due to publication requirements, figures in theprinted version of this article provide panchromaticrepresentations.

Planning roads is a multi-stage process—from a broadlook at all the contributing factors (spatial and non-spatial), to the definition of a corridor (preliminaryalignment) for the general route and, finally, the pre-cise placement of the road centerline. As more infor-mation becomes available in the preliminary planningstage, these processes become increasingly complex. Astechnology progresses, more types of information willbecome available during the preliminary planning stageand even more factors may therefore need to be consid-ered for planning. Eventually, the public will demandthat some or all of these new factors are also included ina “wise” planning process, hence planning processes canbe expected to become more complex in the future andplanners will likely be faced with additional challenges.Even subtasks of the planning process, such as locatingcorridors and drafting initial alignments, are complex,iterative undertakings, requiring the planners to assess,weigh, and evaluate many different factors.

Some of the factors affecting planning alternatives areconnected to “hard” rules and regulations and can betied to monetary values (costs): land value, engineeringexpenses, operations cost, impact on agricultural landuse, and predicted annual road maintenance, etc. Forexample, the American Association of State Highwayand Transportation Official’s (AASHTO) “Policy onthe Geometric Design of Highways and Streets,” the

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 3

Fig. 1. Spatially overlapping GIS data layers.

so-called Green Book, establishes engineering guide-lines (rules) for the basic geometric design of the physi-cal features of a road. State departments of transporta-tion base much of their design manuals on the GreenBook.

However, planners also need to consider less tangiblefactors such as a scenario’s impact on environmentallysensitive areas and how this impact can be mitigated by“trade-offs” (i.e., making up for habitat lost as the resultof new construction), future expandability, and socialjustice. Further, the context of the design is very im-portant and is considered increasingly when local con-siderations warrant adaptations of design standards (see“Flexibility in Highway Design,” 1997). A general plan,such as the connection of two towns with a new high-way, has, in practice, multiple “spatial solutions” (so-called alternatives) depending on how much certain fac-tors are impacted. To evaluate these different solutions,it is standard practice to create a qualitative evaluationmatrix. From such a matrix, each factor may be quanti-fied and given a weight depending on its “expense” (im-

pact). The weighted sum of each solution may be calcu-lated and the final values of all the solutions can then becompared. However, the quantification of some factorsis often controversial (safety, environmental, etc.), mak-ing commensuration difficult. Therefore, factors may beleft in raw form and decision makers must then base de-cisions on the implicit value of each. Figure 4 shows anexample evaluation matrix form for the environmentalfactors of a project.

Although this method allows non-specialists to rankthe available solutions and to choose among the win-ners, the matrix method also requires the planning spe-cialists to assess the impact of these less tangible factorsand to create weights that reflect the right priorities. Asthis is clearly a very difficult undertaking, the compara-bility of two solutions with the same final values and thedesignation of “the best solution” of the solution withthe best final value may be questionable.

There are a few prototypes of automated (algorith-mic) computer-optimized solutions, such as Scaparraand Church (2005) and Jha et al. (2001); however,

4 Harding & Souleyrette

Fig. 2. GIS vector data (forest, rivers, towns, and roads).

Fig. 3. Typical use of a traditional GIS for highway location planning purposes with multiple layers of spatial data shown(courtesy of Iowa DOT).

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 5

Fig. 4. Two examples of an environmental assessment matrix to evaluate alternative planning solutions.On the left: a qualitative matrix (Wisconsin DOT); on the right: a quantitative matrix (Iowa DOT).

because of the complexity of the situation and thesometimes ill defined nature of the rules of the planningprocess, these automated solutions can only be usedduring a few well-defined planning steps. For example,an automated system could provide the planner with op-timized solutions for minimizing construction and oper-ating costs, which could then be imported into a GIS.However, the majority of planning work is still based onthe planners’ expertise and understanding of the largersituation, that is, expert knowledge and past experiencewith similar cases.

However, current GIS planning tools and procedurescan make it difficult to incorporate such expert knowl-edge and experiences efficiently. For example, the digi-tizing of a corridor for the general route requires plan-ners to visually integrate spatial data from several GISlayers although simultaneously applying several rules.Only a limited number of the many potentially rele-vant GIS layers can be combined before the resultingvisual becomes confusing; simply displaying all layers atonce is likely to cause information overload and visualclutter.

A planner could instead selectively view only a fewof the available layers during the planning task, how-

ever, switching some layers on and others off forces theusers to keep the switched-off layers in memory in or-der to mentally keep track of the full picture. For cer-tain tasks, the expert may quickly require additionalinformation to make an informed spatial decision. Forexample, when digitizing a line onto the topographicmap with the mouse, the user may need to check ifthe current cursor would lie within an open space ora tree covered area and may need to access the landuse data layer. Although a traditional GIS might requirethe user to activate the land use layer and possibly hideother layers to avoid clutter, a multi-sensory GIS systemwould allow the user to look at the topographic map buthear the land use value as different types of sounds (ur-ban vs. nature sounds).

2.2 3D geovisualization and virtual environments

Most of the day-to-day, practical work with geospatialdata and a GIS or a CAD system still uses the famil-iar plan view that mimics a two-dimensional map. How-ever, there is a trend toward visualizing geospatial datawith 3D graphics, as is evident in the development ofapplications such as Google Earth Microsoft’s Virtual

6 Harding & Souleyrette

Earth (3D), NASA’s Worldwind, OSSimPlanet, andESRI’s ArcGlobe (Geller, 2007). More generally, thediscipline of geovisualization combines GIScience, 3Dscientific visualization, information visualization, car-tography, spatial statistics, and visual data analysis. Mc-Master and Usery (2004) states the need for the “devel-opment [of] extensible methods and tools that enableunderstanding of, and insight to be derived from, the in-creasingly large and complex geospatial data sets.”

Although it remains difficult to define preciseboundaries, some forms of advanced 3D geovisual-ization systems could be called geospatial versionsof virtual environments (MacEachren et al., 1999;Zlatanova et al., 2002). A virtual environment (VE)aims to put the user in computer-generated artificialenvironments (Krueger, 1991) by using Virtual Reality(VR) technology—3D graphics with immersive (stereo)vision and real time interactivity via 3D interaction de-vices. Such specific interfaces are needed for VR toenable the user to interact with this non-existing, vir-tual environment. Interface technology for VR typicallygoes beyond the traditional mouse/keyboard paradigmand may even employ multiple types of senses to re-ceive and/or create information, such as multi-sensoryhuman-computer interfaces, which are also called multi-modal interfaces (MMIs). These modes refer to the var-ious modes of human sensory perception (vision, sound,touch, etc.) and are not to be confused with the var-ious travel modes often considered by transportationengineers.

2.3 User interfaces that employ multiple senses(multi-modal interfaces)

During the past few years, the open space of multi-modal interfaces has received a lot of attention and ismotivated by the desire to create novel and possiblymore effective user interfaces (Oviatt, 2003). An inter-face may use different sensory modalities (visual, audi-tory, tactile, and olfactory) to communicate informationto the user (Ramloll et al., 2000; Golledge et al., 2006)and/or to receive information from the user, for exam-ple, via speech, pen, touch, gaze, or gestures (Oviatt,1999, Althoff et al., 2001). Multi-modal interface de-sign draws on research from the cognitive sciences, suchas Miller’s (1956) work on memory and chunking orWickens’ (2002) work in attentional resource models.Multi-modal theories seem to suggest that by channel-ing information through multiple senses, more informa-tion can be processed simultaneously and potentiallymore effectively. Advantages of multi-modal input in-clude a reduction in time needed and errors made anda decrease in mental load (Oviatt, 1999; Vitense et al.,

2003). Benefits of multi-modal information presenta-tion (output) include the merging of mutual informa-tion from several modalities (synergy, data fusion), in-creased robustness via redundant mapping of the sameinformation to several modalities, and increased per-formance due to increased sensory bandwidth (Sarter,2002). Jeong and Gluck (2003) report increased perfor-mance for a spatial analysis task in a multi-modal GIS.

2.4 Haptics and sonification

Computer haptics (Srinivasan and Basdogan, 1997)refers to the simulation of touch via a software/hardware combination. Simplistically, haptics may bedivided into two types: skin-pressure related (tac-tile) and position related (kinesthetic). A PHANToM(SensAble Technologies, Inc., Woburn, Massachusetts)(Figure 5) is a grounded point-haptic device with forcefeedback from the stylus’ tip that enables haptic percep-tion (output) and interaction (input) via a single point—the tip of its stylus (Figure 6).

Although the PHANToM’s stylus/tip provides veryprecise positional feedback, it affords only minute tac-tile (skin) feedback. Typically, users adapt quickly tousing this somewhat unrealistic haptic feedback andthere is evidence that it increases their speed and con-fidence for certain activities (see Harding, 2000 for astudy on terrain digitizing). When touching a computer-generated 3D object (say a cube), the user’s touch gen-erates a force. The computer then calculates a counterforce to keep the tip just outside the cube. The PHAN-ToM’s single point force is updated approximately 1,000times per second to create a holistic 3D perception from

Fig. 5. SensAble’s PHANToM force feedback device(Desktop Model).

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 7

Fig. 6. Interacting with a 3D object (dice) via thePHANToM’s tip.

Fig. 7. Co-located system where graphics and hapticsoverlap.

single events. Three-dimensional stereo vision that isco-located with haptics (Stevenson et al., 1999) com-bines visual stereo display with haptic force feedback(Figure 7) into an immersive, multi-modal system.

Beyond the haptic display of 3D shapes (geome-try), the PHANToM can simulate surface properties(with friction or procedural textures, Shopf and Olano,2006) and it can perform real time user-guided objectdeformations (Cani and Angelidis, 2006). It is possi-ble to design innovative new interactions between theuser-held tip and a virtual object—interactions such as

force-snapping, rubber-banding, or attraction/repulsion(gravity). A new $200 device called the Falcon (NovintTechnologies, Inc., Albuquerque, New Mexico) pro-vides a smaller haptic workspace than the $12,000 Desk-top PHANToM or the $2,000 Omni PHANToM (bothmade by SensAble Technologies, Inc.), but could helpto bring interactive 3D force feedback to a mainstreamaudience.

Sonification (Kramer et al., 1999) is the use of non-speech acoustic signals to translate (map) informationinto sound. An example of scientific sonification is tomap numerical data (e.g., temperature or elevation)into sound parameters such as frequency (pitch), am-plitude (volume), tempo (speed), and certain timbreproperties in a way that these sound parameters encodeknowledge about the data values (parameter mapping).For example, in a MIDI piano sonification of numericdata, low data values play low-pitched notes and highdata values play high-pitched notes (Dimitris and Alty,2005) to communicate relative changes of data (falling,rising). Besides mapping data to musical notes (Blattneret al., 1989), sonification also uses real world audio (au-ditory icons, Gaver, 1986) for symbolizing data values—for example, city noises for the data value “city” or wa-ter noises for the concept of water. Although a full the-ory of sonification may not yet exist, the last decade hasseen the establishment of many guidelines for sonifica-tion design (Walker and Kramer, 2005).

2.5 Previous work on multi-sensory geospatialinformation systems

There have been several systems that work with repre-sentations of geospatial data via audio and/or via touch,either to enhance visual systems or to support visuallyimpaired users. Note that most of them use force feed-back mice or force feedback joysticks as haptic displays,not the PHANToM haptic device we use. Work byGriffin (2002) and Jacobson (2002) indicates that hap-tic and audio cues can be effective for representing spa-tial information. The participants in Jacobson’s studyused interactive scanning and probing techniques to ex-plore a surface. Scanning was useful for finding overalltrends in data, although probing was effective at find-ing values at a specific location of interest. Ratti et al.(2004) present a mixed-reality system to interact withGIS data via a tangible user interface. Krygier (1994)presented a system for representing spatial data via re-alistic or abstract sounds that uses analogies to visualiza-tion. Fisher (1994) used the duration of sound to com-municate the reliability of pixels on a remotely sensedimage. Zhao (2005) reported on the sonification of spa-tial information (choropleth maps) and suggested that

8 Harding & Souleyrette

the Shneiderman visualization mantra (Shneiderman,1996) should also be considered when exploring spa-tial information via sound. Jeong and Gluck (2003) pre-sented results of a feasibility study testing the perfor-mance of various identification tasks on a GIS withadded haptic and auditory displays. Haptic displays pro-duced faster and more accurate performance than au-ditory displays and combined displays for more com-plex tasks. Harding (2000) and Harding et al. (2002)report on an earlier multi-sensory system for investi-gating geoscientific data, such as using a PHANToMto digitize fault lines on a digital model of the seaflooron which multiple geophysical properties (grids) hadbeen mapped. A predecessor to our current system wasused for hapto-visual suitability analysis (Harding andNewcomb, 2004), a simple, generic process for dealingwith the local suitability (rated on a scale of one to ten)for various geospatial planning scenarios. In this systemwe used the PHANToM to generate haptic gravity ef-fects that pull the user in the direction of higher suit-ability and push users away from areas of lower suit-ability. The computer science aspects and some of thepreliminary results of the multi-sensory road planningsystem were published in the proceedings of a sym-posium on visual computing (Newcomb and Harding,2006).

3 METHODS: TECHNOLOGY USEDIN OUR SYSTEM

Our system offers the user the interactive data explo-ration of overlapping spatial data via vision, haptic,and audio and the ability to create new line segments(new roads) during this exploration. We use a DesktopPHANToM, a grounded haptic force feedback device,and the ReachIn System (ReachIn, 2007) (Figure 8), tosimulate an impenetrable horizontal plane for the userto touch and to draw on.

This seems to us as an intuitive metaphor for drawinglines on a paper map lying on a table. To explore thedata contained in this map and to draw the new roadonto this map, the user grasps the PHANToM’s styluslike a pen and moves it within the workspace. Althoughthe map is flat, the user can move the stylus in all threedimensions; the PHANToM’s workspace is roughly a 40cm cube. Note that there is no way to pan, zoom, or ro-tate the map. The position of the stylus’ tip is trackedwithin the workspace and is actively controlled by thePHANToM’s three motors with a maximum force of7 N (for the Desktop model of the PHANToM). ThePHANToM’s force feedback occurs when the tip comesinto contact with a virtual 3D object—in our setup, thesimulated map table. If the user attempts to put the sty-

Fig. 8. Our planning system on the mirrored ReachInSystem. The user looks into the mirror at a virtual map (solidline) and touches it with the stylus (dotted line). To the user,

both worlds overlap spatially.

lus tip down on the table, the tip will attempt to pene-trate the horizontal plane from above. The PHANToMrecognizes this and its motors push the tip, and withit the user’s hand, upwards to just above the horizon-tal plane. Because these checks and corrections happencontinuously every 1/1000th of a second, the user’s mo-tor system (hand) and visual system are tricked to be-lieve in a continuous, solid boundary. In addition to theshape (geometry) of a 3D object, we use effects such asattraction (gravity) or friction to describe more fully thehaptic properties of 3D objects. For example, the terrainelevation map is not only hard but also has the propertyof friction, which lets us define how difficult it is to movethe tip over the map. We can vary the friction value atdifferent areas of the map so that some areas feel likerubber and other areas feel like metal.

Figure 9 shows the user’s view of this virtual map.The user interface buttons to the right are used to de-fine the assignment of a data layer to one of the threesensory modalities (vision, touch, sound) to the threedata layers (thus creating a “visual” layer, a “sound”,layer, and a “touch” layer), such as visual: terrain, au-dio: land use, touch: roads. The buttons also provideundo and start-over (reset) functions for drawing thenew road. As the users make contact with the map,they can feel a force representation of the “haptic” datalayer but they can also see a “visual” data layer as atraditional map (and the tip’s current location on it)

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 9

Fig. 9. A screenshot of the user’s view of the system including the map (elevation model), the user interface buttons, andthe stylus.

and they can hear a “sound” representation (sonifica-tion) of the sound data layer (a sound stream). When incontact with the map, the users may activate a buttonon the stylus (comparable to clicking a mouse-button)to activate the pen’s ink—this will draw a new roadonto the map, although still providing force and audiofeedback.

Although the visual layer can represent the full maparea at once, the haptic and sound representations canonly represent the point on the map that is currentlyunder the tip. As the user moves this tip, the touchand sound representations change according to whichvalue is “under the tip.” This distinction between thevisual representation and the touch/sound representa-tion is necessary because of the technology availableand because of differences in sensory perception. Al-though the users are able to, at least subjectively, graspthe map’s content visually, the PHANToM’s technologylimits haptic perception of the content to a tiny “virtualfingertip.” Sweeping this virtual fingertip over the sur-face may afford the user to perceive larger structures.However, the complexity of the structures conveyed viathis fingertip are very limited and cannot compare to theinput provided by the human hand, which draws muchinformation from the skin’s receptors.

Similarly, the human auditory system is not geared to-ward such a broadband perception, but rather to pro-cess signals along the temporal domain, for example,in a melody. Although it would be technically possible

to generate a sound expression that represents the to-tality of the data contained in the sound layer (equiva-lent to the visual expression as a map), the users wouldlikely be unable to comprehend the content. We there-fore chose to represent the content of the sound layeras a sequence of musical tones, each corresponding tothe data under the tip, which means that the touchchannel and the sound channel are both results of theuser touching (probing) the map with a virtual finger-tip. Given our ability to process large amounts of visualdata very quickly, such low-bandwidth data input mayhardly seem useful, however (a) these two data streamscan represent data that is currently not visible and (b)as they are tied to the user controlled tip, their forceand sounds are intuitively understood as responses tothe user’s interactions with the map.

4 DATA USED IN THE USER STUDY OF THEROAD PLANNING SYSTEM

The data used in our study of a road planning systemrepresents a 10 km by 10 km area in Iowa and is amix of raster data (terrain elevation and land use) andvector data (existing major roads and gravel roads) aswell as a combination of categorical and numerical data.Terrain elevation and distance-to-nearest-road (whichis needed for the road’s touch and sound representa-tions) are numerical data layers (both in meters). Land

10 Harding & Souleyrette

Fig. 10. Existing roads (center lines) with buffer zones (left panel) and an audio/haptic representation of the buffers (right panel).

Fig. 11. Visualization of land use data visually via colors (left panel) and an audio/haptic representation (right panel).

use is a categorical data layer with four classes: city,river, wooded area, and cropland. The following will dis-cuss the three different sensory representations (visual,haptic, and sound) for each of these data layers (terrainelevation, land use, and existing roads).

4.1 Visual layers

For the visual terrain layer, a 10 m resolution digi-tal elevation model (DEM) is colored with a smoothblue–yellow–red color scale to communicate the pro-gression of elevation from low values to high values(see Figure 9). In addition, we created a semitranspar-ent hill shade layer, with a simulated sun coming fromthe Northwest (315◦) that accentuates the slope gradi-ents. We overlaid this hill shade layer on all visual lay-ers; this provided the users with a visual reference forthe terrain and helped them put locations on the mapinto their spatial context. The existing roads layer is a

combination of line data (green for gravel roads, red forhighways) and buffer zones around them. Gravel roadswere given a 50 m buffer, although highways have a red50 m buffer plus a 100 m purple buffer (Figure 10, left).In the visual land use layer, the four types of data valueswere given commonly used colors: red for cities, blue forrivers and lakes, green for wooded areas and yellow foropen space (Figure 11, left).

4.2 Haptic (touchable) layers

We used three different haptic effects, depending onthe type of data presented. Terrain elevation (a nu-meric variable) is presented directly via “haptic bumpmapping,”—the lower the elevation the more the tipsinks in, whereas it is raised gradually for higher ele-vations. After some early tests, we calibrated the differ-ence from the lowest elevation to the highest elevationto feel like a difference of 1 cm, enough to let the users

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 11

perceive subtle features and to let them feel valleys orcrests by running the tip over the surface.

To tell the user about the distance to existing roads(again a numerical variable) in a haptic way, we set upa haptic gravity open space. If the tip touches the mapand is within a road’s buffer zone, the tip is attractedperpendicularly toward the closest road. This attractionforce is kept constant within a buffer. However, majorroads have a stronger attraction force than minor roads.If the users simply follow this “suggested” force vector,the tip is guided to follow the most important road inrange. Again, we used early tests to scale the rate ofchange in force magnitude appropriately; the “width”of the gravity zone corresponds to the buffers shown inFigure 10, right.

To express the land use maps via touch, we createda friction map (Figure 11, right) where each pixel’svalue represents the haptic equivalent to distinct “hap-tic color.” We use suitably different values (based ona power series) to create different degrees of “sticki-ness” (surface friction). For this haptic rendition of thedifferent types of land use (open space, wooded area,river valley, and urban) we order the degree of stick-iness according to “planning-suitability”: open spaceshave the lowest friction and thus convey that they arewell suited for building a road, wooded areas (green),rivers (blue) and cities (red) have higher friction to con-vey that it would be more expensive to build there. Ad-mittedly this superposition of an ordering is contrary tothe concept of the pure categorical data type, however,it is very difficult to create the haptic equivalent of theconcept of hue in visual colors. A better approach couldbe to use haptic textures and not just friction. Despitedocumented problems in differentiating textures via apoint-haptic device such as the PHANToM (with itslack of skin pressure feedback), it could be possible todesign a haptic “wooded area texture” that can be dis-tinguished from a haptic “open space texture.” As ex-isting roads were already expressed via magnetic forces,they did not need to be conveyed via friction.

4.3 Sound (audio) layers

For the sound (audio) layers, again we mapped the nu-merical data differently from the categorical land usedata. We created three different “audio maps” whereeach pixel contains sound information that is inter-preted depending on the meaning of its data. For nu-merical data (terrain elevation and distance-to-road) weuse real time MIDI sounds with only pitch changes;pitch coding of numerical values capitalizes on the ear’sability to perceive increasing and decreasing pitch/dataand seemed to be a good starting point for this sonifi-cation (Flowers, 2005). For terrain we increased pitch

with elevation increase. After experimenting with dif-ferent mapping granularities (continuous, semi-tones,whole tones, fifths, octaves), we used whole tones (1 oc-tave) from low to high; this granularity allows the usersto hear approximately level terrain as a steady pitch andis reasonably pleasing to most ears. We also used pitchand sound volume to communicate buffer distance inthe existing roads layer. Once the tip is inside a bufferzone, the pitch and volume start high and decrease withproximity to the road. Limiting the occurrence of soundto within the buffer zones helped to clarify the spatialrelationship; however, spatial (surround) audio wouldhave been useful to express distance together with di-rection.

The land use data offered us the opportunity to ex-periment with mapping the concept contained in a cat-egory (town, wooded area) into a literal, “real world”sound. We created “sound snippets” (similar to auditoryicons, Gaver, 1986) that use sound typical for the envi-ronments they are meant to symbolize: branches snap-ping and bears for wooded area, people talking and carshonking for towns, insects chirping and wind for openplains, and running water for rivers. We mixed in someambient noises but found it important to start each snip-pet with a “key signature” sound (honk, cricket). Asa snippet will continue to play as long a certain typeof land use is touched, the snippets are designed toloop around and are fairly long (up to 20 seconds). Seewww.vrac.iastate.edu/∼charding/snippets for examplesof different sounds.

5 A USER STUDY OF A MULTI-SENSORY ROADPLANNING SYSTEM

5.1 Setup of the user study

We know of no systems for interactive data explorationof road planning data via vision, haptic, and audio. Aswith any new innovation, there are many questions andthey should be centered around users. We have al-ready discussed the system’s vision, its technology, itsdata, and its functionality. In this section we focus onsome user centered questions, which help to assess thesystem’s value to the users, or at least to future re-searchers. General questions include: Does the new sys-tem work as intended? How well does the system work?Is the new system substantially better than existing so-lutions? Is it faster? These types of questions may beanswered by a user study (or user evaluation), which,in turn should be based on a task analysis (Kirwanand Ainsworth, 1992). The user study may be mainlyqualitative and document the way each user succeedsor fails to perform the task, or it may measure time,

12 Harding & Souleyrette

success rate, and even a user’s mental load or stresslevel. The analysis, qualitative or statistical, of the userstudy helps to reveal fundamental flaws and is useful toguide further development of the system (Sanders andMcCormick, 1993).

The fact that there is hardly any prior experience withcreating and using a visual/haptic/auditory road plan-ning system prompted us to limit the initial scope ofour user study to a qualitative study. Using a fairly sim-ple three-data layer multi-modal system, this study at-tempts to answer the question, “Given a simple but typ-ical task, how do users work with this new system?” Inother words, we wanted to initially observe the system“in action” and confirm that the users could deal witha completely novel way of accessing spatial data andrecording their feedback. The results of this should behelpful in improving system design and pave the wayfor further, quantitative studies of users’ performance,error rates, mental work load, etc. Statistical analysis ofthese quantitative measurements can then be used toquantify the advantages of multi-sensory systems overconventional systems.

We asked 12 upper-level civil engineering students totest the system. The students were paid for their timeand received course credit. The students had each com-pleted a semester-long highway design class and had ex-perience performing similar tasks on similar spatial datausing a traditional GIS. The students started by fillingout questionnaires about their background and level ofknowledge (Table 1). None of the users had any seri-ous visual or hearing impairments. The task given to thestudents was to plan a road between two predeterminedpoints by drawing on a virtual map and by using theirroad planning knowledge and several GIS data layers.In our study, we deliberately limited the data used toonly three layers: terrain elevation, land use, and exist-ing roads. Table 2 shows the resulting six different com-binations of data layer type with sensory modality (i.e.,the layer’s “display” mode).

After filling out the questionnaire, we familiarized thestudents with the data in general and allowed them toexperiment with each of the six data-modality combina-tions, typically for a total of 15 minutes. We made surethey understood that although they could only look atone of the three data layers at a time, they were ableto “display” the other two layers via touch and soundand should experiment with finding suitable combina-tions of the three layers depending on what they neededto accomplish for each subtask. We recorded eachstudent’s voice and videotaped the computer screenduring the test, which used a think-aloud protocol(Lewis and Reiman, 1993), that is, we encouraged thestudents to tell us what they were thinking during thetest and to explain their reasons for planning the align-

Table 1Results of the pre-test questionnaire (summarized)

Average age Average of 24 yearsGender 2 female, 10 maleHighway design related

activitiesTypically 6 months to 2 years

Years of experience withGIS

Typically 6 month to 2 years,mostly with ArcView

Experience with virtualreality or haptics

None

Years of musical activity(instrument, singing)

2–8 years

Table 2The six possible combinations of presentation mode (display

type) and data layer type

Visual display Haptic display Sound display

1 Terrain Roads Land use2 Terrain Land use Roads3 Roads Terrain Land use4 Roads Land use Terrain5 Land use Terrain Roads6 Land use Roads Terrain

ment in a certain way. These recordings were later usedto analyze each user’s test.

After reiterating the main rules for road planningto the student (e.g., make the road as short as possi-ble, avoid going through difficult terrain, re-use existingroads if possible, cross existing roads at near right an-gles, etc.), we started the actual test by bringing up thelocation of two towns on the virtual map. The locationsand GIS data layers were identical for each student andthe data set was different, but conceptually very similarto a case the students had been trained on in class viatraditional maps and GIS. We set no time limit for com-pletion of the task and left it up to the student where tostart and which strategy to use to digitize the new road(i.e., to plan the road in one long stretch or by connect-ing several smaller pieces). We also allowed the studentsto erase parts and to start over if they changed theirminds. The actual test part typically took 15 minutes tocomplete (actual duration varied from 660 seconds to1,300 seconds). The following are some excerpts of theaudio transcripts captured during the test via the think-aloud protocol:

User A: “Ok, I’m going to keep my visual layeron roads so I can keep them at 90 degrees, so I’mgoing to put touch on the terrain, and I’m goingto put sound on the land use. I’m going to followthe existing interstate going north and then I’m

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 13

going to make a curve that cuts across 90 degreesat these existing roads and then just make a largeradius curve that connects. I think it’s essential tocut here where the river is at the shortest lengthas possible because that’s expensive, the largestcost of making a road is going to be the bridge.So now, I see the terrain, touch is the roads, assound I want to have land use so I’ll know whatI’m going through as I scroll over it.”

User B: “So basically if I’m planning on buildinga road from this town to this town, and I want tomake it as short as possible and cost efficient. I’mgoing to choose the smallest area over this riverhere. So, with the terrain on audio I’m going tohead south over this. Basically as I push down Ican hear what I am going to go over.”

User C: “Ok, so I know by touch when I the ma-jor highway first and let me find it here. There’sa little drag in here. Ok, so I’m connected to aroad right here. And I can feel the terrain gostraight down here and there is a little hill and alittle dip and then basically there is even ground.So, I’m having a combination of the visual show-ing roads and the touch for terrain and the soundfor land use. It’s a great combination for finishingthis map because as I go across I can tell wherethe wooded area is coinciding with the valley andthe terrain and that helps me decide when goingjust straight.”

Tester: “Ok, so can you tell me what sort of stuffyou started looking at first, what were you look-ing for?” User D: “I was looking for the longestsection that didn’t have a very big change in ele-vation, and then I checked the land use to makesure I wasn’t in too much of the valley, I was try-ing to avoid water at all, but have the possibilityof going into the city.” Tester: “So, did you havetwo steps, basically getting that one big stretchand then trying to cross the river? So why didyou draw that first section there?” User E: “Well,visual was land use, touch was for terrain, thesound was for roads. It felt pretty good throughthere, so I thought it would be pretty flat and itlooked like it was a straight shot. It just seemedlike a good starting point. Let’s go to land usefor touch for a minute, no, I’ll keep it on terrain.I’m just going to check this terrain and see if Idid remember the valley right. OK, now I’ll dothe touch layer on roads and I’ll do the sound onterrain.”

After the completion of the test, each student filledout a short exit questionnaire. They were asked to rank

Table 3Results of the post-test questionnaire with number of

students choosing a certain answer

Which sense was most useful inthe planning process?

Vision: 10, Touch: 2

Which data layer was the mostimportant in the planningprocess?

Terrain: 9, Land Use: 3,Roads: 1

What is the best sense to workwith Terrain?

Touch

What is the best sense to workwith Land Use?

Sound

What is the best sense to workwith Roads?

Vision

the senses and the data by importance and to assigntheir favorite data layer/sensory modality combinationaccording to the experience they had gathered duringthe test of the system.

Table 3 summarizes the main responses to the ques-tions. We also asked the students to tell us what theyliked and disliked about the system and to give ussuggestions for improvement they might have. The sys-tem was generally perceived as completely different,novel, and even “cool,” especially the haptic componentwith its ability to feel the terrain elevation and attractionforce toward existing roads. Most students commentedthat the sound used for the distance-to-existing-roadlayer was much less intuitive than the sound used forland use layer. Many students wished they could havelooked at more than one layer at once, a constraint weput in place to keep the number of layers low and toencourage the students to think about how to use thenon-visual senses. Altogether, the study took each stu-dent around 45 minutes to complete.

5.2 Results of the user study

Besides generally gathering data about user behavior,we looked at three research questions in particular:

• What data-modality combinations did the subjectsprefer during the task?

• Did the subjects have a strategy for switching be-tween different data-modality combinations?

• Was the visual sense used for global orientationand navigation, and were the haptic/audio sensesused locally to “add-value” while digitizing?

Table 4 shows the total time that the students spentwithin each of the possible six combinations of data lay-ers to sensory modalities. Terrain elevation was usedmostly in its haptic mode, which may reflect its abilityto find and stay in flat areas or valleys. Land use data

14 Harding & Souleyrette

Table 4Modality (vision, touch, and audio) users assigned to each

data layer; in % of total time

Visual display 27% 32% 41% 100%Haptic display 66% 23% 11% 100%Sound display 24% 42% 34% 100%

was preferred in its sound mode, which may reflect theease of recognition of auditory icons (audio symbols),although the existing roads layer was preferred in thevisual mode. These observations correspond with thesubjective answers the students gave when asked to picktheir favorite sensory modality for each data layer.

We also created timeline diagrams for each subjectthat show which sensory modality was used to “display”which data layers during the test (time is given in sec-onds). For example, User 3 initially configured the sys-tem to display Land Use to feel terrain and to hear roads(Figure 12). We analyzed these 12 timelines, the video-tape recording and the transcripts of the audio record-ings for common strategies (or patterns) for switchingbetween data-modality configurations during the testand found most users falling in one of two groups—“lazy switchers” and “explorers.”

Figure 12 shows examples of typical switching be-havior for the first group. This group was characterizedby few switches, which occurred primarily in the visualchannel. It seems these users decided early on which

Fig. 12. Timeline diagrams of data layer (color) vs. sensory modality (group 1, “lazy switchers”).

data layers should be mapped to haptic and audio andsaw little need to change these mappings during the test(e.g., see User 12). Again, it was typical to use hapticsto display the terrain elevation, listen to land use, and tolook at existing roads. The transcripts seem to indicatethat these users planned the road in bigger sections, thatis, starting at one point and working toward the otherpoint. When they perceived the need to react to compli-cations, such as how to approach a river, they reconfig-ured their mappings. It should be noted that this recon-figuration was typically initiated by a switching of thevisual mapping, and that the new combination was typi-cally kept for a while. On average there were only threeto four data switches for the non-visual channels andfour to six switches for the visual channel for this group,who employed little sensory redundancy (i.e., display-ing the same data layer via two senses). It should benoted that there was no obvious correlation betweenthis group and GIS expertise, in other words userswith more experience in using the tradition (visual-only) GIS did not necessarily use a low number ofswitches.

Figure 13 shows some examples of the second groupwith its typical switching patterns. In general these usersseemed to explore the different possible mappings inmore detail than members of the first group. Theytended to “play around” with different combinations,including redundant combinations. These users typi-cally did not develop their alignment in one continuous

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 15

Fig. 13. Timeline diagrams for members of the second group (“explorers”).

move from one town to the other. Although theyseemed to have a general idea about the setup of theirnew road, they often used the multi-sensory nature ofthe system to help them approach challenging designareas first. Because it was not immediately clear whichcombinations of mappings would work best for a cer-tain challenge, they were willing to experiment with dif-ferent combinations of perceiving the data layers viadifferent sensory modalities. Once they had fixed (par-tial) alignments in the challenging design area, they thenconnected them into an overall alignment.

After studying the videotapes and going over the au-dio transcripts made from the think-aloud recordings,we believe that there are indications that our systemgrants the user two different “perspectives” on the threedata layers. The users seemed to be able to developand retain a sense of global orientation and all usersseemed to have developed a global mental plan (“starthere, then go here, avoid this, and end up here”) basedon vision. Some of the visual-only switching (especiallyin users from Group 2) seems to reflect a desire to re-gain a situational awareness of a data layer that hasnot been used for a while or to “look at what’s ahead”when following a mental plan. More importantly for ourpurposes are indications that the addition of touch andsound via a single point of contact does create a con-glomerate of several senses on a local level: during thedrawing, visual information about one data layer canbe augmented by haptic and audio information fromthe other layers and help users to find the right path.

The most successful augmentation seems to come fromperceiving changes in land use via sound or perceivingchanges in terrain elevation via haptics and adds a senseof global orientation by superimposing those changesover a visual map.

Although the result of this study may only be validwithin the very specific context for this task (alignmentplanning), with this data set (terrain, land use, roads),and a generalization beyond this context is problematicuntil more experience with multi-sensory informationsystems (MSISs) can be gathered, this study representsa first step toward the augmentation of established en-gineering procedures via MSISs.

6 LIMITATIONS

Because of the exploratory nature of the system, thestudy was limited in several ways. Although it wouldbe technically possible, we did not calculate by howmuch each student’s alignment planning was differ-ent from an optimal alignment created by an expert.However, all students had created a fairly logical so-lution to the posed problem and their results were vi-sually reasonably similar. Quantitative results (beyondthe total time taken by each student) that would allowus to honestly compare the solutions provided by thedifferent students are thus not possible. For the sake ofsimplicity we artificially limited the study to three GISlayers and added the caveat that each of these layers

16 Harding & Souleyrette

must always by “bound” to a different sensory-modality(one to visual, one to haptic, and one to audio). We thusprevented them to purely visually combine all three lay-ers, which is, of course, a very common way of workingwith a traditional GIS. To be able to compare the multi-sensory system with traditional GIS we would also haveto run the study with the same data and setup but lethalf the users work with a traditional GIS system in-stead. However, given the fundamental differences be-tween the two setups, it would be doubtful if one couldindeed construct two equivalent cases, thus potentiallylessening the power of such a comparison.

7 FUTURE WORK

Our prototype multi-sensory information system is be-ing improved based on the feedback from the study.Technical improvements include a redesign of the waythat roads can be perceived via touch and via sound,enhanced functionality for interaction with the virtualmap and for drawing and customization of the way datavalues are mapped (transformed) into force and soundeffects.

Although the use of gravity is useful to convey thedirection to the nearest road (including the “snapping”effect), conveying the road’s distance via the amountof force proved problematic because it had to be firstlearned and then remembered by the user. A bettermethod may be to use a small number of “steps” that areset up as multi-buffers around roads (e.g., 500 ft, 250 ft,and 0 ft away). Each step would be highlighted by aminute snap or a change in friction, on top of the gravity

Fig. 14. Tilted terrain (3D view) and elevation-to-audio transform function (left panel).

effect. The sound representation of the distance fromthe tip to the nearest road is now based only on musi-cal tones, where higher pitch means higher distance. Al-though generating a voice output that reads the actualdistances (“500–250 ft,” etc.) could be more useful, itmay become annoying to listen to. Expressing a precisedirection via sound is difficult and would require a 3Daudio setup. It is possible to generate surround soundvia headphones or with a set of loudspeakers and use itto make the sound or voice seem to come from the di-rection to the nearest road; however, a good calibrationof such a surround system is still not trivial. It seems thata combination of touch and sound would be a better wayto express such data; the direction would be expressedvia force vector and the distance could be expressed viapitched tones or via voice.

The current system is deliberately set up as a 2D,top-down map view inside a 3D space. The next logi-cal step is to not only allow the user to pan and zoomthis map but to also tilt (rotate) this map (shown rightin Figure 14). This would increase the spatial perceptionof the terrain (especially if 3D stereo glasses were to beused). Zooming in (Figure 15), would allow the user tofocus on parts of the map when drawing.

We are also experimenting with customizing the pa-rameters that govern the transformation of a value un-der the tip’s location to a sound or a force (the multi-sensory equivalent to tweaking the colors and symbolsfor a visual representation of GIS data as a map). Anexample is the elevation-to-audio widget shown left inFigure 14, which allows the user to interactively de-fine a function for transforming the incoming elevation

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 17

Fig. 15. Zooming in for drawing with more detail.

values (x-axis) into audio parameter values. The blackline shows how the tones’ pitch rises in steps with in-creasing elevation and the straight gray line shows theirchange in volume (sound pressure).

A major next goal should be to establish a better un-derstanding of which multi-sensory techniques shouldbe best used to communicate certain types of spatiallayers (and certain types of data) via touch and soundand to catalog which techniques work for which typeof GIS data and for which tasks. Although there isample knowledge about communicating spatial datavisually from the fields of cartography and visualiza-tion, an equivalent catalog of best practices will beneeded for touch and sound to avoid unnecessary re-experimentation and user testing for each new datalayer or new task. The current study has given us someindications of these best practices, for example, that ter-rain elevation seems well represented by force effectsthat mimic the ups and downs of the terrain; however,more work is needed with regard to other types of GISdata layers and the setup of their internal parameters.Further testing with a more realistic and complex ex-ample, the development of measures of effectivenessto test improvements facilitated by multi-sensory plan-ning, and the development of testing and proceduremanuals should also be next steps.

Compared to the growing use of 3D computer graph-ics to visualize geospatial data, haptic and sound con-tinue to play only a very limited role. Although theavailability of reasonably priced haptic force feedbackhardware has increased in recent years, there is still a

lack of real-world applications that leverage its capa-bilities. Similarly, despite the availability of compara-bly high-quality sound systems in most computer sys-tems, there are still very few software applications whichactually realize the potential for data sonification. Wespeculate that the principal barriers to more widespreaduse of non-visual presentation of geospatial informa-tion is (a) a lack of easy to use tools for incorporat-ing touch and sound into existing software systems and(b) the lack of knowledge about rules for creating in-tuitive, effective, and customizable user interfaces withtouch and sound. In addition to fundamental research,there is a need to find additional well-defined prob-lems, which can be solved more effectively by augment-ing existing systems with non-visual methods. In thearea of highway location planning, the augmentationof systems for planning alternative, computationally de-rived alignments, which help to examine alterationsto “optimal” designs, could present an opportunityfor further research into multi-sensory, interactivesystems.

ACKNOWLEDGMENTS

We acknowledge the contributions of Matt Newcombto the implementation of the system and the study. Weare grateful for the expertise provided by staff of theIowa DOT in Ames and the feedback and suggestionsfor improvements provided by the reviewers.

18 Harding & Souleyrette

REFERENCES

AASHTO (2001), Policy on the Geometric Design of High-ways and Streets, 4th edn., American Association of StateHighway and Transportation Officials (AASHTO).

Althoff, F., McGlaun, G., Schuller, B., Morguet, P. & Lang,M. (2001), Using multimodal interaction to navigate in ar-bitrary virtual VRML worlds, in Proceedings of the 2001Workshop on Perceptive User Interfaces (Orlando, Florida,November 15–16, 2001), PUI’ 01, vol. 15. ACM, New York,NY.

Blattner, M. M., Sumikawa, D. A. & Greenberg, R. M. (1989),Earcons and icons: their structure and common design prin-ciples, ACM SIGCHI Bulletin, 21(1), 123–24.

Cani, M. & Angelidis, A. (2006), Towards virtual clay, in ACMSIGGRAPH 2006 Courses (Boston, Massachusetts, July30 – August 03, 2006), SIGGRAPH’ 06. ACM Press, NewYork, NY, 67–83.

Dimitris, I. R. & Alt, J. L. (2005), The rising pitch metaphor:an empirical study, International Journal of Human-Computer Studies, 62(1), 1–20.

FHWA: Flexibility in Highway Design (1997), U.S. Depart-ment of Transportation, Federal Highway Administration(FHWA), Available online at: http://www.fhwa.dot.gov/environment/flex/.

Fisher, P. (1994), Animation and sound for the visualizationof uncertain spatial information, in H. M. Hearnshaw andD. J. Unwin (eds.), Visualization in Geographic Informa-tion Systems, John Wiley and Sons, Chichester, England.

Flowers, J. (2005), Thirteen Years of Reflection on AuditoryGraphing, in Proceedings of the ICAD 2005, Limerick,Ireland.

Gaver, W. (1986), Auditory icons: using sounds in computerinterfaces, Human-Computer Interaction, 2, 167–77.

Geller, T. (2007), Imaging the world: the state of onlinemapping, IEEE Computer Graphics and Applications,March/April, 27(2): 8–13.

Golledge, R. G., Rice, M. & Jacobson, R. D. (2006), Mul-timodal interfaces for representing and accessing geospa-tial information, in S. Rana and J. Sharma, (eds.), Frontiersof Geographic Information Technology, Springer-Verlag,Berlin and New York, pp. 181–208.

Griffin, A. L. (2002), Feeling it out: the use of haptic visu-alization for exploratory geographical visualization, Carto-graphic Perspectives, 39, 12–29.

Harding, C. (2000), Multi-sensory investigation of geoscien-tific data: adding touch and sound to 3D visualization andmodeling, Ph.D. Thesis, University of Houston.

Harding, C., Kakadiaris, I. A., Casey, J. F. & Loftin, R. B.(2002), A multi-sensory system for the investigation of geo-scientific data, Computers and Graphics, 26(2), 259–69.

Harding, C. & Newcomb, M. C. (2004), Supporting interactivedata exploration for GIS planning tasks with a multi-modalvirtual environment, in Third IEEE Workshop on Haptic,Audio and Visual Environments (HAVE) 2004, Montreal,Canada, pp. 81–86.

Iowa DOT: Environmental Assessments (2001), A how-tomanual, prepared for: Iowa department of transportation,Prepared By: Earth Tech, June, 2001.

Jacobson, R.D. (2002), Representing spatial informationthrough multimodal interfaces: overview and preliminaryresults in non-visual interfaces, in Conf. on Information Vi-sualization: Symposium on Spatial/Geographic Data Visu-alization, IEEE Proceedings, London, 10–12 July, 2002,pp. 730–34.

Jeong, W. & Gluck, M. (2003), Multimodal geographic infor-mation systems: adding haptic and auditory display. Journalof American Society for Information Science and Technol-ogy, 54(3), 229–42.

Jha, M. K., McCall, C. & Schonfeld P. (2001), Using GIS,genetic algorithms, and visualization in highway develop-ment, Computer-Aided Civil and Infrastructure Engineer-ing, 16(6), 399–414.

Kirwan, B. & Ainsworth, L. K. (1992), Guide to Task Analysis,Taylor and Francis Group, London, UK.

Kramer, G., Walker, B., Bonebright, T., Cook, P., Flowers, J.,Miner, N. & Neuhoff, J. (1999), Sonification report: statusof the field and research agenda, Report prepared for theNational Science Foundation.

Krueger, M. W. (1991), Artificial Reality II, Addison-WesleyPublishing, Reading, MA.

Krygier, J. B. (1994), Sound and geographic visualization, Vi-sualization in Modern Cartography, pp. 149–66.

Lewis, C. & Reiman, J. (1993), Task Centered User InterfaceDesign: A Practical Introduction, University of Colorado,Boulder, CO (shareware web book).

MacEachren, A. M., Edsall, R., Haug, D., Baxter, R., Otto,G., Masters, R., Fuhrmann, S. & Qian, L. (1999), Virtualenvironments for geographic visualization: potential andchallenges, in Proceedings of the ACM Workshop on NewParadigms in Information Visualization and Manipulation,Kansas City.

Mark, D. M. (2003), Geographic information science: defin-ing the field, in Foundations of Geographic Information Sci-ence, Chapter 1, Taylor and Francis Ltd, London, UK.

McMaster, R. B. & Usery, E. L. (2004), A Research Agendafor Geographic Information Science, CRC Press, Boca Ra-ton, FL, p. 402.

Miller, G. A. (1956), The magical number seven plus or minustwo: some limits on our capacity for processing information,Psychological Review, 63, 81–87.

Newcomb, M. C. & Harding, C. (2006), A multi-modal inter-face for road planning using vision, haptics and sound, inProceedings of the International Symposium of Visual Com-puting (ISVC) 2006, Lake Tahoe, CA, pp. 417–26.

Oviatt, S. (1999), Ten myths of multimodal interaction, Com-munications of the Association of Computing Machinery(ACM), 42(11), 74–81.

Oviatt, S. L. (2003) Multimodal interfaces, in J. Jacko and A.Sears (eds.), The Human-Computer Interaction Handbook:Fundamentals, Evolving Technologies and Emerging Appli-cations, Lawrence Erlbaum, Mahwah, NJ, pp. 286–304.

Ramloll, R., Yu, W., Brewster, S., Riedel, B., Burton, M.& Dimigen, G. (2000), Constructing sonified haptic linegraphs for the blind student: first steps, in Proceedings of theFourth International ACM Conference on Assistive Tech-nologies, Assets’ 00. ACM Press, New York, NY, pp. 17–25.

Ratti, C., Wang, Y., Ishii, H., Piper, B. & Frenchman, D.(2004), Tangible user interfaces (TUIs): a novel paradigmfor GIS (2004), Transactions in GIS, 8(4), 407–21.

ReachIn (2007) http://www.reachin.se/ (accessed 12-21-07).Sanders, M. & McCormick, E. (1993), Human Factors In En-

gineering and Design, McGraw-Hill, New York, NY, ISBN:0-07-054901-X.

Sarasua, W, Simas de Oliveira, M. G., Carroll, B. & Troemel,D. (1999), Traffic impact analysis by using geographicinformation system technology, Transportation ResearchRecord, 1999, issue 1660, pp. 84–91.

Sarter, N. B. (2002), Multimodal information presenta-tion in support of human-automation communication and

Investigating the use of 3D graphics, haptics (touch), and sound for highway location planning 19

coordination, in E. Salas. (ed.), Advances in Human Per-formance and Cognitive Engineering Research, JAI Press,New York, pp. 13–36.

Scaparra, M. P. & Church, R. L. (2005), A grasp and path-relinking heuristic for rural road network development,Journal of Heuristics, 11, 89–108.

Shneiderman, B. (1996), The eyes have it: a task by data-typetaxonomy for information visualizations, in Proceedings ofthe 1996 IEEE Symposium on Visual Languages (VL’96),IEEE Computer Society Press, Boulder, CO, pp. 336–43.

Shopf, J. & Olano, M. (2006), Procedural haptic texture, inProceedings of the 19th Annual ACM Symposium on UserInterface Software and Technology, Montreux, Switzerland,October 15 – 18, 2006, UIST’ 06. ACM Press, New York,NY, pp. 179–86.

Srinivasan, M. A. & Basdogan, C. (1997), Haptics in virtualenvironments: taxonomy, research status, and challenges,Computers and Graphics, 21(4), 393–404.

Spear, B. D. & Laksmanan, T. R. (1998), The role of GIS intransportation planning analysis, Geographical Systems, 5,45–58.

Stevenson, D., Smith, K., McLaughlin, J., Gunn, C.,Veldkamp, J. P. & Dixon, M. J. (1999), Haptic work-bench: a multisensory virtual environment, in Proceedings

of SPIE—Volume 3639 Stereoscopic Displays and VirtualReality Systems VI, 1999, San Jose, CA, pp. 356–66.

Vitense, H. S., Jacko, J. A. & Emery, V. K. (2003), Multimodalfeedback: an assessment of performance and mental work-load, Ergonomics, 46, 68–87.

Walker, B. N. & Kramer, G. (2005), Sonification design andmetaphors: comments on Walker and Kramer, ICAD 1996.ACM Trans. Appl. Percept., 2(4), 413–17.

Wickens, C. D. (2002), Multiple resources and performanceprediction, Theoretical Issues in Ergonomic Science, 3(2),159–77.

Wisconsin DOT: State of Wisconsin, Department of Trans-portation, Facilities Development Manual, Procedure 23-45-5—Information Required in Environmental Docu-ments; https://trust.dot.state.wi.us/static/standards/fdm/23/23-45-5.pdf Accessed 12/3/2007.

Zhao, H. (2005), Interactive sonification of geo-referenceddata, in CHI’ 05 Extended Abstracts on Human Factorsin Computing Systems (Portland, OR, USA, April 02-07,2005), CHI’ 05. ACM Press, New York, NY, pp. 1134–35.

Zlatanova, S., Rahman, A. A. & Pilouk, M. (2002), 3D GIS:current status and perspectives, in Proceedings of the JointConference on Geo-spatial theory, Processing and Applica-tions, 8–12 July, 2002, Ottawa, Canada.

Dossier – Appointment as Full Professor Reginald R. Souleyrette. Ph.D., P.E.

Sample of Work – Exhibit E

A COMPARISON OF TECHNIQUES TO COLLECT VEHICLE OPERATIONAL DATA 1 

AND DEVELOP TRAJECTORIES AND SPEED PROFILES THROUGH 2 

HORIZONTAL CURVES 3  4 

Eric J. Fitzsimmons1, Shashi S. Nambisan2, and Reginald R. Souleyrette3 5 

6 

7 

8 1Graduate Research Assistant and Corresponding Author 9 Department of Civil, Construction, and Environmental Engineering 10 Iowa State University, 326 Town Engineering Building, Ames, Iowa 50011 11 Phone: 515-294-5860, Fax: 515-294-8216 12 Email: efitz@iastate.edu 13  14  15 2Professor and Director of the Institute for Transportation 16 Department of Civil, Construction, and Environmental Engineering 17 Iowa State University, 2711 South Loop Drive, Suite 4700, Ames, Iowa 50010 18 Phone: 515-294-5209, Fax: 515-294-0467 19 Email: shashi@iastate.edu 20  21  22 3Gerald and Audrey Olson Professor of Civil Engineering and 23 Associate Director of the Institute for Transportation 24 Department of Civil, Construction, and Environmental Engineering 25 Iowa State University, 2711 South Loop Drive, Suite 4700, Ames, Iowa 50010 26 Phone: 515-294-5453, Fax: 515-294-0467 27 Email: reg@iastate.edu 28  29  30  31  32 Submission Date: August 1, 2010 33 Number of Words in Text: 4,972 34 Number of Tables / Figures: 2,500 35 Total Equivalent Number of Words: 7,472 36  37  38  39  40 

Submitted for presentation and publication at the 41 90th Annual Meeting of the Transportation Research Board 42 

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Fitzsimmons et al. 2010

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ABSTRACT 1 Horizontal curves present drivers with numerous tasks that, if not performed while approaching 2 

and negotiating the curve, may result in a roadway departure crash. A vehicle’s lateral position 3 

within the lane and its speed are two indicators of interest from safety and operational 4 

perspectives. These can be measured simultaneously at multiple locations along the curve. 5 

However, researchers face the challenge of collecting operational data while minimizing impacts 6 

on driver behavior, and developing robust, efficient, and accurate means to obtain the data. This 7 

paper presents the findings of a series of pilot studies on closed and open courses that 8 

investigated the effectiveness and accuracy of pneumatic road tubes and digital video cameras 9 

for collecting such data. These devices generally intended for other various purposes in traffic 10 

engineering. Closed-course studies investigated a single data collection station setup, while an 11 

open-course study investigated multiple data collection stations on a horizontal curve. The data 12 

were reduced manually and automatically, and tests were performed to evaluate the statistical 13 

significance of the analyses. The results of the pilot studies showed that pneumatic road tubes 14 

provided a higher level of accuracy than video data. Mean vehicle trajectories and 85th 15 

percentile speed profiles were also created. Furthermore, it was found that drivers moved away 16 

from the edge o the travel lane in the presence of the video equipment, and the nighttime speeds 17 

being nominally lower than daytime speeds. Vehicle speeds at the center of the curve were also 18 

noted to be lower when seven sets of pneumatic road tubes were used compared to only two sets 19 

of road tubes being used. 20 

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INTRODUCTION/BACKGROUND 1 Vehicle crashes at horizontal curves have been recognized for many years as a considerable 2 

safety problem. Campbell et al. (2008) explained that drivers are faced with multiple tasks while 3 

approaching and traversing a horizontal curve. They also noted that between the point of 4 

curvature (PC) and the center of the curvature (CC), important tasks that must be carried out 5 

include keeping proper lane position and speed. Staplin et al. (2001) suggested that most 6 

horizontal curve crashes result from a lack of controlling these tasks, which could lead vehicles 7 

to drift within their lanes and potentially off the roadway. To investigate how well drivers 8 

perform these tasks, trajectory and speed profiles can be created using data collected in the field. 9 

One of the most important aspects of collecting field data is to test the limitations and 10 

effectiveness of the data collection equipment. The aim of this paper is to present the 11 

groundwork and proof of concept for selected equipment typically used. 12 

13 Identifying a vehicle’s lateral position within the lane and its speed are common data collection 14 

practices in transportation research fields such as work zone studies, studies of streets with 15 

bicycle lanes, and roadway shoulder design. Typical equipment utilized for this are pneumatic 16 

road tubes/piezo strips and video cameras. Researchers have successfully used video data 17 

collection for a variety of situations, including estimating roadside encroachment (Miaou and 18 

Lum, 1993), lateral placement, speed distributions, and lane keeping at curved sites (Miles et al., 19 

2006). Davis and Pei (2005) have also developed a robust methodology to collect video data of 20 

crashes on highway segments and use of sophisticated software to reconstruct vehicle 21 

trajectories. Video based observations require a good vantage point to place the camera, either an 22 

elevated position or a camera positioned on a raised pole. 23 

24 

Pneumatic road tubes and piezo strips have also been utilized extensively as an economical way 25 

to collect vehicle operational data when a high vantage point is not available. Pneumatic tubes 26 

have been utilized to evaluate countermeasure safety and determine whether drivers react to the 27 

countermeasure by increasing their lateral distance away from the edge line and changing their 28 

speed at one or two points (Chrysler, 2009; Krammes and Tyer, 1991; Finley et al., 2008; 29 

Donnell et al., 2006). However, these studies generally utilized only one or two data collection 30 

points at the countermeasure and did not fully develop a trajectory and speed profile through a 31 

curved or straight tangent segment of roadway. 32 

33 A review of the literature identified limited research that specifically investigate ways to 34 

construct vehicle trajectories and speed profiles at horizontal curves without the aid of a high 35 

vantage point at the site and advanced software packages to reduce the data. Two previous 36 

studies attempted to bridge this research gap. Park et al. (2003) created vehicle trajectories and 37 

speed profiles at 12 curves in South Korea using seven digital cameras and Nu-metric plates set 38 

up along the horizontal curves. Spacek (1998) used infrared delineator posts at six horizontal 39 

curves in Switzerland to collect vehicle operational data. These were used to develop seven 40 

distinct vehicle trajectories through horizontal curves. However, there is a need to evaluate the 41 

effectiveness and relative accuracies of equipment used typically to determine the lateral position 42 

and speed of vehicles traversing horizontal curves. An approach to address this need is presented 43 

herein. 44 

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Fitzsimmons et al. 2010

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RESEARCH APPROACH 1 On a general level, the underlying methodology for creating a vehicle trajectory and speed 2 

profile is to trace individual vehicles through a roadway section and then plot their speed and 3 

lane position against time or location. This process can be complicated in rural settings, where 4 

high vantage points or areas to set up equipment and draw power may be limited or non-existent. 5 

However, researchers have utilized pneumatic road tubes and video cameras to collect and 6 

reduce vehicle operational data such as vehicle type, speed, lateral distance, gap, and wheelbase 7 

length. This study examined and compared these two types of equipment and developed a 8 

methodology for effectively obtaining key speed and trajectory data with these devices at 9 

horizontal curves. Closed- and open-course studies were utilized to test these methodologies and 10 

determine the variables that could be collected and the variables’ accuracy. Data obtained from 11 

pneumatic road tubes and video cameras were compared against manual measurements of the 12 

tire location. 13 

14 

Closed-Course Studies 15 

Background 16 

Two closed-course studies were conducted to test the effectiveness and accuracy of pneumatic 17 

road tubes set up in a “z” configuration for collecting lateral distance data, as illustrated in Figure 18 

1 (Cottrell, 1986; Dudek et al. 1988; Mahoney et al. 2003; Miles et al. 2005). Pneumatic road 19 

tubes operate on the principle that when a wheel compresses the tube, a time-stamp is recorded 20 

by the traffic classifier (accurate to a thousandth of a second). As Figure 1 shows, the data 21 

collection setup is 16 feet long, with two perpendicular tubes at either end and a single diagonal 22 

tube between the two. The tubes are extended from the edge of the roadway to the center of the 23 

roadway. 24 

25 

26 FIGURE 1 Z-configuration setup of road tubes. 27  28 

A careful installation technique must be followed to ensure that the pneumatic road tubes are 29 

properly secured and stretched tightly across the roadway; poor installation will give false or 30 

inconclusive readings. Air in the tube travels in two directions as the compression occurs, hitting 31 

either the tube pinched off by the other tire on the same axle, the end of the tube, or the traffic 32 

Fitzsimmons et al. 2010

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classifier. Setting up the tubes perpendicular to the roadway provides a single air pulse to the 1 

traffic classifier and gives a high accuracy rate in determining vehicle speed and classification. If 2 

a speed study was being conducted using only two tubes, the time stamp chronological sequence 3 

for the two tubes (Tubes 1 and 2) for a two-axle vehicle would be 1122. This sequence indicates 4 

Tube 1 detected the vehicle’s front axle, then the rear axle followed by Tube 2 detecting the front 5 

and rear axle. If three tubes are installed (Tubes 1, 2, and 3), the error-free chronological 6 

sequence would be 13312332. However, due to the unsteady state of the air pulses along the 7 

diagonal tube, chronological sequences can be a variation of the previous sequence, including, 8 

for example, 1333212333323 or 132331332, which are valid observations to extract lateral 9 

distance. 10 

11 

To determine vehicle lateral distance from time-stamp-based data and trap dimensions, and 12 

assuming that the diagonal tube was installed to make a right triangle, the following equation can 13 

be utilized (Chrysler, 2009): 14 

15 

Eq. 1 16 

Where: 17 

Oy = Vehicle lateral distance from the pavement marking to the outside front tire of the vehicle 18 

L = Length over the entire setup (16 feet) 19 

L4 = Distance between Tube 1 to the point where Tube 3 intersects the reference line (typically 20 

the inside of the pavement marking) 21 

ti = Time-stamp recorded at each tube 22 

W = Width of the travel lane 23 

Wd = Length of the diagonal tube from the pavement marking to the centerline 24 

25 

Generally, the procedure to reduce vehicle lateral distance data involves multiple steps of data 26 

cleaning and filtering. Along with collecting data from three tubes, a speed study can be 27 

performed at the same time by utilizing the time-stamp data from the two perpendicular tubes. A 28 

custom macro to apply Equation 1 to the present study’s data set was created based on a macro 29 

developed by researchers at the Texas Transportation Institute (Johnson, 2008) to analyze piezo 30 

strips in a z-configuration. The macro identifies individual vehicles based on large gaps in the 31 

running time-stamp data; separates the vehicles and extracts the first 1, 3, and 2 of the 32 

chronological sequence for each vehicle while disregarding any other time-stamp data in the 33 

sequence; and applies Equation 1. 34 

35 

The results of the lateral distance data extraction can easily be compared to the speed study data. 36 

The speed study is used to identify unknown vehicle classifications, and the macro often 37 

identifies these vehicles as well. When the lateral distance data and speed data are combined, the 38 

unknown vehicle data are discarded. The previous vehicle data are also discarded because the 39 

data for this vehicle likely tripped the unknown classification. Finally, outlier data are removed, 40 

including vehicles well over 100 mph and vehicles whose width is beyond the lane width. The 41 

following is a summary of the experiment to enable comparisons of data obtained from the 42 

pneumatic road tubes with manual measurements of the tire position in the lateral direction. 43 

44 

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Fitzsimmons et al. 2010

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Experiment Design 1 

The first closed-course study was performed in a closed parking lot, as illustrated in the top left 2 

of Figure 2. The course was a tangent section 240 feet long with 180 feet of acceleration 3 

distance. Vehicle speeds were kept to less than 35 miles per hour. The second closed-course 4 

study was performed on a closed roadway with plenty of acceleration and deceleration distance, 5 

and vehicle speeds were kept under 55 mph. A total of 36 observations were made and recorded 6 

at each location. 7 

8 

9 

10 FIGURE 2 Closed course setup (parking lot - top left, on closed city street – top right) and 11 

crushed limestone aggregate ridge (bottom images) 12  13 

In addition to using the pneumatic road tubes to obtain Oy, manual measurements were used to 14 

compare the data. As illustrated in the bottom of Figure 2, a crushed limestone aggregate ridge 15 

was placed adjacent to Tube 1 of the setup to help measure with a tape measure the lateral 16 

distance from the edge line, Ob. The ridge was reset after every observation. This method proved 17 

to be an excellent way to imprint where the vehicle’s passenger-side tires passed as the vehicle 18 

moved through the trap. 19 

20 

Analysis and Results 21 

The lateral distance data collected by the pneumatic road tubes were then compared to the 22 

manual measurements. A matched-pair statistical analysis was used with the assumption that the 23 

Tire Position

Fitzsimmons et al. 2010

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data sets’ two distributions were similar, though not normally distributed because the research 1 

team was in control of the speed and lateral position of the car. A paired t-test was selected 2 

because the statistical model is robust when analyzing similar distributions. The null hypothesis 3 

tested that the mean difference between observations is zero at a 90 percent level of significance. 4 

Table 1 shows the results of the analysis. 5 

6 

TABLE 1 Analyses of the Closed-Course Studies 7 

8  9 

Two important observations can be extrapolated from Table 1. First, the paired t-test indicated 10 

that the pneumatic road tubes, with the aid of the macro for data reduction, provide accurate 11 

measurements. Second, the accuracy of these measurements hold true for a broad range of 12 

vehicle speed ranging from 19 to 51 mph. These suggest that the results will hold true for an 13 

even higher speeds. 14 

15 

OPEN-COURSE STUDIES 16 

Background 17 

The objective of the open-course studies was to utilize the methodologies verified in the closed-18 

course study and apply them to typical conditions at a horizontal curve. The secondary objectives 19 

included the following: 20 

Determine a systematic methodology to trace vehicles through a system of seven z-21 

configured pneumatic road tube setups on the outside lane of the curve 22 

Investigate the accuracy and effectiveness of video-based data collection compared to 23 

pneumatic road tubes for individual speeds and lateral distances 24 

Plot mean vehicle trajectories and 85th percentile speed profiles from PC to CC and 25 

determine statistically significant changes 26 

Investigate whether equipment presence and the amount of equipment affects driver 27 

behavior and when based on the data collected by each type of equipment 28 

29 

A two-lane horizontal curve in Ames, Iowa, was selected as a test site for the open-course study. 30 

The horizontal curve provided a safe area for the researchers. It has a radius of 1,146 feet and 31 

length of 1,137 feet. The geometry has travel lanes are separated at the CC by a double yellow 32 

center line and then diverge with the aid of a painted median to a left turning lane at the PC of 33 

the curve, as shown in Figure 2. The posted speed limit is 45 mph for the outside lane. 34 

Countermeasures installed proximate to the horizontal curve include an upstream curve warning 35 

sign and chevron alignment signs. 36 

37 

Experiment Design 38 

The study was conducted over a two-weekday time frame using types of equipment, z-39 

configured pneumatic road tubes and a mobile video trailer. The mobile video trailer, as 40 

illustrated in the right image of Figure 3, consists of a four-channel digital video recorder that 41 

captures video from two cameras positioned at a lower elevation and two elevated cameras 42 

Fitzsimmons et al. 2010

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located 30 feet above the ground. Video was captured at 30 frames per second in .mp4 format 1 

and stored on internal memory. 2 

3 

The left side of Figure 3 shows the setup utilized at the horizontal curve. Data were collected and 4 

reduced from the PC to the CC in the outside lane using seven sets of z-configured pneumatic 5 

road tubes were installed 100 foot intervals. Opposing vehicle traffic was not considered for this 6 

experiment. Three days prior to utilizing the seven sets of pneumatic road tubes, baseline data 7 

were collected with pneumatic road tubes set up at the PC and CC. The pneumatic road tubes 8 

operated for 19 hours and captured both daytime and nighttime traffic. The video trailer was 9 

utilized during the daylight hours only and set up at the CC on the gravel shoulder, 10 

approximately 4 feet from the edge of the pavement. The video trailer was present at the curve 11 

for approximately 6 hours. 12 

13 

14 FIGURE 3 Study setup (left) and digital video trailer (right) at the study site 15 

16 

Road Tube Data Preparation 17 

To be able to trace a vehicle through a set of pneumatic road tubes, it was imperative that the 18 

internal traffic classifiers’ clocks were synchronized. However, similar to other research studies 19 

that utilized traffic classifiers together, this study also noted clock drift over the 19 hours of data 20 

collection. Stations 2 and 6, which included two traffic classifiers manufactured during the same 21 

time period, experienced a clock drift up to 3 minutes, while the other five traffic classifiers 22 

experienced a 10 to 40 second clock drift. Stations 2 and 6 also produced a greater amount of 23 

data with errors, and it is suspected that mechanical issues were affecting the data collection 24 

process. 25 

26 

Data of interest were extracted using the process described in the previous section. Vehicles were 27 

traced through the curve from station to station by aligning the adjusted clock, wheelbase length, 28 

speed, and vehicle type. Over the 19 hours of data collection, data for a total of 1,586 vehicles 29 

were collected by most of the counters. To be included in the final dataset, a vehicle must have 30 

been detected by all seven counters, a condition that brought the total number of vehicles to 31 

1,391. Finally, this data set needed to consist of only free-flowing vehicles. A free-flowing 32 

Elevated 

Cameras 

Low‐Level 

Cameras 

Fitzsimmons et al. 2010

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vehicle is defined as having a minimum headway of 15 seconds. A total of 438 vehicles did not 1 

condition, thus yielding a final data set of 953 vehicles, or 60 percent of the original data set. 2 

3 

Digital Video Data Preparation 4 

Two Autoscope AIS cameras located on top of a 30 foot mast above a trailer were utilized for 5 

this test. Because two cameras could not monitor seven pneumatic road tube stations, it was 6 

decided that Camera 1 would focus a single station at a time and Camera 2 would monitor two 7 

stations at a time. A total of 65 vehicles were captured at each station by both cameras, with a 8 

target number of 50 free-flowing vehicles for further analysis. A total of 653 daytime free-9 

flowing vehicles were manually extracted including vehicles that were deleted from the 10 

pneumatic road tube observations. Extraction was performed by creating a scale based on the 11 

known lane width of the station, and then the lateral distance was measured off of the front 12 

pneumatic road tube at each station, as illustrated in the left image of Figure 4. 13 

14 

15 FIGURE 4 Manual data reduction and automated speed detection 16  17 

The data reduction process proved to be time consuming work; an average of five minutes per 18 

vehicle was used to stop the video and take a measurement. The accuracy of the measurements 19 

depended greatly on the researcher’s best estimate of the outside of the tire, and such variables as 20 

vehicle shadows and the estimated time when the vehicle hit the pneumatic tubes needed to be 21 

overcome. To verify the distances measured by one analyst, two other analysts also performed 22 

the data reduction process, and the results compared. 23 

24 

Data Analysis and Summary 25 

To determine the accuracy of the data collected by the digital video based only on individual 26 

vehicle lateral distance, a matched-pair comparison was used to test the accuracy of the digital 27 

video against the pneumatic road tube data. For comparison purposes, it was assumed that the 28 

pneumatic road tubes provided the most accurate measurement short of physically measuring the 29 

vehicles during the video data collection process. Data were extracted from the pneumatic road 30 

tube set for each video segment, and data sets were created for both cameras. As shown in Table 31 

2, two analyses were performed for both Camera 1, which investigated only one station, and 32 

Camera 2, which investigated two stations at once. 33 

34 

35 

36 

Fitzsimmons et al. 2010

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TABLE 2 Analyses of Pneumatic Road Tube and Video Data for Equal Means and 1 

Medians for Lateral Distance 2 

3  4 

First, the average difference was determined between the video observations and pneumatic road 5 

tube observations. The null hypothesis tested whether the mean difference between observations 6 

was zero using a 95 percent confidence level. A Shapiro-Wilk test was performed on the average 7 

difference distribution to determine normality, and if the distribution was normal, a two-tailed 8 

paired t-test was performed. If the distribution was found to be non-normal, the non-parametric 9 

test of matched-pairs Wilcoxon sign rank was performed. This test is equivalent to the paired t-10 

tests, except the test is investigating the shift in distributions based on the change in medians. 11 

12 

As shown in Table 2, generally the data collected by the pneumatic road tubes and digital video 13 

were normally distributed. However, the p-values for both the parametric and non-parametric 14 

tests showed the means and medians of the distributions to be statistically different at the 95 15 

percent confidence level. It should be noted that during the pneumatic road tube raw data 16 

reduction a higher than usual error rate was found in the traffic classifiers at Stations 2 and 6. 17 

This error is believed to have affected the results presented in Table 2; however, further analysis 18 

is needed to verify this proposition. Finally, the Camera 2 analysis identified four station 19 

observations showing non-normal data distributions, and over half of the station observations’ 20 

distribution means were found not to be equal. It can be concluded that the video data showed a 21 

maximum difference of 3 feet, and the statistical analysis showed overall that the pneumatic road 22 

tubes were collecting more accurate lateral distance data. 23 

24 

It should be noted that at least 2 out of every 50 observations in each data set collected by the 25 

pneumatic road tubes in the z-configuration were off by more than 2 feet. This finding was 26 

confirmed by the video data analysis and error checked in the macro. Further analysis is needed 27 

to fully understand this error in the data collection setup. 28 

29 

To determine the accuracy of the data collected by the digital video cameras based only on 30 

individual vehicle speed, a matched-pair comparison was used to test the accuracy of the 31 

Fitzsimmons et al. 2010

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automated vehicle extraction against the pneumatic road tube speed data. Individual vehicle 1 

speed data were automatically extracted from the video by use of Autoscope processing 2 

software. Two analyses were performed for the present study, including automated speed data 3 

collection of 47 observations at a single station and 46 observations each at two stations, as 4 

illustrated in the right image of Figure 4. Tape, to define detection zones, was placed manually 5 

on top of the pneumatic road tubes, and the detection area was created based on visual inspection 6 

of the camera’s viewing area along the curve geometry. The results of the analyses are shown in 7 

Table 3. 8 

9 

TABLE 3 Analyses of Pneumatic Road Tube and Video Data for Equal Means and 10 

Medians for Speed 11 

12  13 

The automated vehicle speed detection data were compared to the pneumatic road tube data. The 14 

null hypothesis tested whether the mean difference between observations is zero using a 95 15 

percent confidence level. As shown in Table 3, the minimum, maximum, and average speed 16 

differences are quite high. A Shapiro-Wilk test was performed on the average difference 17 

distribution and revealed that both cameras’ two datasets were not normally distributed. 18 

Parametric and non-parametric tests were performed on the observation distributions, and these 19 

tests showed that the distribution means between the video data and pneumatic road tube data 20 

were not equal. Comparing the two types of equipment in terms of collecting and reducing 21 

vehicle speed, the video data automated extraction provided different values for vehicle speeds 22 

than the pneumatic road tubes found. It is believed that due to the curve geometry and viewing 23 

height of the cameras, it was difficult for the Autoscope processing software to accurately detect 24 

vehicles. Further analysis would be needed to confirm this by testing multiple observation 25 

angles. 26 

27 

Mean Trajectory and 85th Percentile Speeds 28 

Based on the closed- and open-course studies, pneumatic road tubes in a z-configuration were 29 

found to be more accurate for collecting individual vehicle lateral distance and speed data; 30 

additionally, other variables of interest could also be extracted from the same data set. Using the 31 

free-flowing data set collected by the pneumatic road tubes at the open-course study site and 32 

known daylight times, the data were categorized into day and night observations. Additionally, 33 

data for the periods when the video trailer was present at the curve during the daytime were 34 

separated out. Illustrated in Figure 5 is the 85th percentile speed for the open-course study site. 35 

36 

Fitzsimmons et al. 2010

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  1 FIGURE 5 85th percentile speed profile for combinations of equipment and time of day 2  3 

As shown in Figure 5, the posted speed limit for the horizontal curve was 45 mph. Results for 4 

three types of equipment are shown, including the baseline: two pneumatic road tubes (shown in 5 

dark and light red), seven pneumatic road tubes every 100 feet (shown in dark and light blue), 6 

and seven pneumatic road tubes with the video trailer present (shown in green). As illustrated, 7 

85th percentile vehicle speed decreased as vehicles approached the CC (station 0). It can also be 8 

shown that, when the data collected with two pneumatic road tubes are compared to the data 9 

collected with seven tubes, the number of pneumatic road tubes, as well as with the presence of 10 

the video trailer, had an impact on 85th percentile speed. A t-test was performed on the data 11 

collected with seven road tubes. From day to night, the decrease in 85th percentile vehicle speed 12 

was found not to be statistically significant at each station However, the speed decrease from 13 

Station 2 to Station 0 for data collected with seven road tubes during the daytime compared to 14 

data collected with seven road tubes in the presence of the video trailer were found to be 15 

significant. Overall, based on the collected data, it was found that the density of data collection 16 

equipment had an effect on driver behavior in terms of the overall decrease in 85th percentile 17 

speed, especially near the CC by about 2 mph. 18 

19 

Using the same pneumatic road tube data and the time of day variable, mean vehicle trajectories 20 

and one standard deviation were plotted along the horizontal curve. Figures 6 and 7 illustrate the 21 

results of the study. The x-axis is the lateral distance from the edge of the pavement marking (0 22 

feet) to the center line of the roadway (approx. 12.5 feet). The y-axis is the distance away from 23 

the CC, with 0 feet being the CC and 600 feet being the PC. In the figures, a purple “ideal” 24 

trajectory was inserted into the plot as well. The ideal trajectory is defined as the path taken by a 25 

six foot wide vehicle’s front passenger tire if it were to travel exactly in the middle of the lane 26 

along the curve. 27 

28 

29 

45

46

47

48

49

50

51

52

53

54

55

0100200300400500600

85th Percentile Vehicle Speed, m

ph

Longitudinal Distance Upstream from Center of Curve, Feet

Posted Speed Limit

2 Tubes Day

2 Tubes Night

7 Tubes Day

7 Tubes Night

7 Tubes Day with Trailer

Sta. 6 

Sta. 5 

Sta. 4 

Sta. 3 

Sta. 2 

Sta. 1 

Sta. 0 

Fitzsimmons et al. 2010

13  

1 FIGURE 6 Mean lateral distance and one standard deviation for daytime 2  3 

4 FIGURE 7 Mean nighttime versus daytime lateral placement for seven pneumatic road 5 

tubes 6  7 

As shown in Figure 6, the daytime average lateral distance from the outside pavement marking 8 

for all types of equipment deviated from the ideal line towards the center of the roadway. 9 

Furthermore, it can clearly be seen that vehicles moved closer to the centerline as they 10 

approached the video trailer from 200 feet away, as illustrated by the green line. This result 11 

shows that the trailer parked on the gravel shoulder affected the lateral position of the vehicles as 12 

they traversed the curve. 13 

0

100

200

300

400

500

600

0 2 4 6 8 10 12 14

Longitudinal Distance Upstream

 from 

Center of Curve, Feet

50th Percentile Distance from Edge Line, Feet

Center line

Ideal

2 Tubes Day

7 Tubes Day

7 Tubes Day with Trailer

7 tubes SD

7 tubes with Trailer SD

0

100

200

300

400

500

600

0 2 4 6 8 10 12 14

Longitudinal Distance Upstream

  from Center 

of Curve, Feet

50th Percentile Distance from Edge Line, Feet

Center line

Ideal

7 Tubes Night

7 tubes Night SD

7 Tubes Day

7 Tubes Day SD

Fitzsimmons et al. 2010

14  

Illustrated in Figure 7 is a comparison of daytime and nighttime data collected by the seven 1 

pneumatic road tubes, with one standard deviation and the ideal trajectory. As shown, the 2 

average lateral distance of the vehicles at night is closer to the center of the roadway than for 3 

vehicles during the daytime. The daytime trajectories were closer to ideal. As stated earlier, 4 

opposing vehicles were not taken into consideration, and most likely the recorded vehicles’ 5 

trajectories would be somewhat different in the presence of opposing vehicles. However, the 6 

plots in Figures 6 and 7 ultimately show that pneumatic road tubes are an excellent means to 7 

collect vehicle operational data and plot vehicle trajectories and speed profiles. Figures 6 and 7 8 

also indicate that data collection equipment does alter driver behavior, though further analysis is 9 

needed to properly quantify the effects. 10 

11 

SUMMARY OF FINDINGS / CONCLUSIONS 12 This paper summarized the results of closed- and open-course studies to test the effectiveness 13 

and accuracy of z-configured pneumatic road tubes and video camera data collection against 14 

actual field measurements. The data evaluated were lateral position and speed. The means of the 15 

distributions were tested for normality and compared using non-parametric and parametric 16 

statistical tests. Finally, vehicle trajectories and speed profiles were developed from these data. 17 

18 

The results of the closed-course studies indicate that the pneumatic road tubes accurately capture 19 

vehicle lateral distance. The results of the open-course study show that vehicles can be traced 20 

through multiple sets of pneumatic road tubes and that video data are not as accurate as 21 

pneumatic road tube data. Additionally, by investigating the changes in mean vehicle trajectories 22 

and 85th percentile speed profiles, driver behavior was shown to be affected by the amount of 23 

equipment present at the roadway. 24 

25 The authors acknowledge that the study had only a small sample size and that further analyses 26 

are needed to quantify the findings. Therefore, caution should be used in applying the results. 27 

28 

ACKNOWLEDGEMENTS 29 The authors wish to thank Dr. Susan Chrysler, Jeremy Johnson, and Jeff Miles of the Texas 30 

Transportation Institute (TTI) for their technical assistance; the Midwest Transportation 31 

Consortium (MTC) and the Institute for Transportation (InTrans) for funding the use of the 32 

traffic classifiers and video trailer; and, finally, the City of Ames, Iowa, for the use of city 33 

roadways for data collection. 34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 

Fitzsimmons et al. 2010

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REFERENCES 1 Campbell, J.L., C.M. Richard, and J. Graham. NCHRP Report 600B: Human Factors Guidelines 2 

for Roadway Systems. HRB, National Research Council, Washington, D.C., 2008. 3 

4 

Cottrell, B.H. The Effects of Wide Edgelines on Lateral Placement and Speed on Two-Lane 5 

Rural Roads. In Transportation Research Record 1069, TRB, National Research Council, 6 

Washington, DC, 1986, pp. 1-6. 7 

8 

Davis and Pei. Bayesian Reconstruction of Median-Crossing Crashes and Potential Effectiveness 9 

of Cable Barriers. In Transportation Research Record 1324, TRB, National Research Council, 10 

Washington, D.C., 2005, pp. 141-148. 11 

12 

Donnell, E.T., M. D. Gemar, and I Cruzado. Operational Effects of Wide Edge Lines Applied to 13 

Horizontal Curves on Two-Lane Rural Highways. Pennsylvania Transportation Institute, 14 

Pennsylvania State University, University Park, 2006. 15 

16 

Dudek, C.L., R.D. Huchingson, F.T. Creasey, and O. Pendleton. Field Studies of Temporary 17 

Pavement Markings at Overlay Project Work Zones on Two-Lane, Two-Way, Rural Highways. 18 

In Transportation Research Record 1160, TRB, National Research Council, Washington, DC, 19 

1988, pp. 22-32. 20 

21 

Finnley, M.D., D.S. Funkhouser, and M.A. Brewer. Studies to Determine the Operational Effects 22 

of Shoulder and Centerline Rumble Strips on Tow-Lane Undivided Roadways. Texas 23 

Transportation Institute, Texas A&M University, College Station, 2008. 24 

25 

Johnson, J. Z-configuration Data Reduction Routines, unpublished computer code, Texas 26 

Transportation Institute, College Station, Texas, 2008. 27 

28 

Krammes, R.A. and K.D. Tyer. Post-Mounted Delineators and Raised Pavement Markers: their 29 

Effect of Vehicle Operations at Horizontal Curves on Two-Lane Rural Highways. In 30 

Transportation Research Record 1324, TRB, National Research Council, Washington, 31 

D.C.,1991, pp. 59-71. 32 

33 

Mahoney, K.M., R.J. Porter, E.T. Donnell, D.Lee, and M.T. Pietrucha. Evaluation of Centerline 34 

Rumble Strips on Lateral Vehicle Placement and Speed on Two-Lane Highways. Report No. 35 

FHWA-PA-2002-034-97-04. Pennsylvania Transportation Institute, University Park, 2003. 36 

37 

Miaou, S. and H. Lum. Statistical Evaluation of the Effects of Highway Geometric Design on 38 

Truck Accident Involvements. In Transportation Research Record 1407, TRB, National 39 

Research Council, Washington, D.C., 1993, pp. 11-24. 40 

41 

Miles, J.D., P.J. Carlson, M.P. Pratt, and T.D. Thompson. Traffic Operational Impacts of 42 

Transverse, Centerline, and Edgeline Rumble Strips. Report No. FHWA/TX-05/0-4472-2. Texas 43 

Transportation Institute, College Station, 2005. 44 

45 

Fitzsimmons et al. 2010

16  

Miles, J.D., M.P. Pratt, and P.J. Carlson. Evaluation of Erratic Maneuvers Associated with 1 

Installation of Rumble Strips. In Transportation Research Record 1973, TRB, National Research 2 

Council, Washington, D.C., 2006, pp. 73-79. 3 

4 

Park, Y-J., C-H. Park, and K-S. Chon. Development of Potential Measures to Evaluate the Safety 5 

of Curves in Rural Highways. KSCE Journal of Civil Engineering, Vol. 7, No.3, 2003, pp. 233-6 

242. 7 

8 

Staplin, L., K. Lococo, S. Byington, and D. Harkey. Guidelines and Recommendations to 9 

Accommodate Older Drivers and Pedestrians. Report FHWA-RD-01-051, U.S. Department of 10 

Transportation Federal Highway Administration, Washington, D.C., 2001. 11 

12 

Spacek, P. Fahrverhalten un Unfallgeschehen in Kurven, Fahrverhalten in Kurvenbereichen. 13 

InStitut Für Verkehrsplanung, Transporttechnick, Strassen- un Eisenbahnbaur, ETH Zürich, 14 

1998. 15 

16 

17 

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