project 5: ramp metering control in freeway system
DESCRIPTION
Project 5: Ramp Metering Control in Freeway System. Team Members: Faculty Mentor: Isaac Quaye Dr. Heng Wei Junior GRA: Emma Hand Kartheek K. Allam Sophomore Jared Sagaga Junior. 2. Sponsor. Grant ID No.: DUE – 0756921. 3. Outline. Introduction - PowerPoint PPT PresentationTRANSCRIPT
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Project 5: Ramp Metering Control in Project 5: Ramp Metering Control in Freeway SystemFreeway System
Team Members: Faculty Mentor:
Isaac Quaye Dr. Heng Wei
Junior GRA:
Emma Hand Kartheek K. Allam Sophomore
Jared SagagaJunior
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SponsorSponsor
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OutlineOutline
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• Introduction
• Scope of study, goals and tasks
• Training
• Data Collection
• Methodology
• Simulation and progress
• Timeline
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National StatisticsNational Statistics
• Average time spent on highway (NHTSA 2009)– Student: 1.3 hours/day
– Working: 1.5 hours/day
– 36 hours/year in traffic
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Source: NHTSA
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National Statistics (cont.)National Statistics (cont.)
• 32,885 people died in motor vehicle traffic crashes in 2010 (NHTSA)– 5,419,000 total crashes on highway, 29% caused injury or were fatal
• 33% crashes occur on freeway stretch with bridges or interchanges (2011)
• $871 BILLION in economic loss and societal harm
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Ramp Ramp
MetersMeters
What can fix this?What can fix this?
Source: Reference 10
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Why Ramp Meters?Why Ramp Meters?
• Reduce congestion
• Improve throughput (up to 62%)– Decrease in time spent staring at break lights
• Reduce travel time (20-61%)
• Improve travel time reliability
• Ensuring safety of vehicles (5-43% decrease in accidents)
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Types of Ramp MeteringTypes of Ramp Metering
• Fixed time
– Pre-timed meter cycle based off of past data
• Responsive
– Meter cycles vary depending on changes in traffic conditions
– Isolated
– Coordinated
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Meters Across the USMeters Across the US
Seattle: 232
Portland: 110
LA: 1478
Phoenix: 122
Salt LakeCity: 23
Denver: 46
Arlington: 5
Minn-St. Paul: 444
Milwaukee: 122
Chicago: 117 New York: 75
N. Virginia: 26
Implemented - Responsive
In Progress - Responsive
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In Progress - Fixed
Ohio: 34
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Scope of StudyScope of Study
• Conducting research on the study site (I-275) by gathering data using traffic counter and GPS device
• Criteria – Elevated locations nearby for placing the camcorder to capture the traffic– Location should be busier in the peak hours than the normal flow of
freeway
• Analyzing traffic during the peak hours• Investigating and observing both a single and two lane ramp
implementation in VISSIM
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GoalsGoals
• Investigate
– Effectiveness of ramp implementation
– One or two lane ramp metering
• Successfully run simulations in VISSIM
• Present and complete deliverables
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TasksTasks
• Generate VISSIM network model using processed data
• Analyze results
• Assemble research findings
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TrainingTraining
• GPS and traffic counting
• VISSIM Software
– Simulation set up
– Data input and analysis
– Calibration
– Validation
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Data CollectionData Collection
I-275
Mosteller RoadReed Hartman
Highway
Study Site
LegendLegendEast-Bound East-Bound
SectionsSectionsWest-Bound West-Bound
SectionsSections
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Data Collection (cont.)Data Collection (cont.)
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Data Collection (cont.)Data Collection (cont.)
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Traffic VideoTraffic Video
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Data Collection (cont.)Data Collection (cont.)
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Sample DataSample Data
9/16/2013 EB09160653 On-ramp Emma 691 55 746EB09160753 On-ramp Jared 636 83 719EB20130916155957 Freeway Isaac 10960 395 11355EB20130916065028 Freeway Jared 10139 797 10936
9/17/2013 EB201309171622 Freeway Isaac 5337 179 5516EB20130917072223 Freeway Emma 7877 497 8374WB20130917070632 Freeway Jared 9175 659 9834
9/18/2013 EB20130918154910 Freeway Isaac 12514 468 12982 WB09181600 On-ramp Emma 621 23 644
EB20130918065700 Freeway Isaac 11860 630 12490
List of Video Completed
Date Video Name LocationStudent Collected Count of videos Total
Cars Trucks
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Data Collection (cont.)Data Collection (cont.)
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QTravel QTravel
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MethodologyMethodology19
VISSIM TrainingVISSIM Training
Simulation Setup
Simulation Setup
Run Simulation
Run Simulation ResultsResults
One Lane Ramp
One Lane Ramp
Two Lane Ramp
Two Lane Ramp
ValidationValidationCalibrationCalibration
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SimulationSimulation
• Calibration– Desired speeds
– Routing decisions
– Driving behavior
• Validation– Speed (+ 10%)
– Travel Time (+ 15%)
– Volume (GEH Statistic)
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ProgressProgress
• Post-Processing data collected
– Analyzing the data collected with the GPS and traffic counting device
• VISSIM
– Running simulations
– Calibration and validation
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Progress (cont.)Progress (cont.)
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Network ModelNetwork Model
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Progress (cont.)Progress (cont.)
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TimelineTimeline
Task Week
1-2 3 4 5 6 7-8
Methods of evaluation and research
Equipment and software training
Data collection and analysis
Use data to develop deliverables
Create and run simulation models
Complete deliverables
Completed
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LegendLegend
CompleteComplete
IncompleteIncomplete
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ReferencesReferences
• Zongzhong, T., Nadeem, A. C., Messer, C. J., Chu, C. (2004). “Ramp Metering Algorithms and Approaches for Texas,” Transportation Technical Report No. FHWA/TX-05/0-4629-1, Texas Transportation Institute, The Texas A&M University System, College Station, Texas.
• Yu, G., Recker, W., Chu, L. (2009). “Integrated Ramp Metering Design and Evaluation Platform with Paramics,” California PATH Research Report No. UCB-ITS-PRR-2009-10, Institution of Transportation Studies, University of California, Berkley, California.
• Kang, S., Gillen, D. (1999). “Assessing the Benefits and Costs of Intelligent Transportation Systems: Ramp Meters,” California PATH Research Report No. UCB-ITS-PRR-99-19, Institution of Transportation Studies, University of California, Berkley, California.
• Arizona Department of Transportation. (2003). Ramp Meter Design, Operations, and Maintenance Guidelines.
• Papamichail I., and Papageorgiou, M. (2008). “Traffic-Responsive Linked Ramp-Metering Control,” IEEE Transactions on Intelligent Transportation Systems, Vol. 9, No. 1, n.p.
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References (cont.)References (cont.)
• Federal Highway Administration, USDOT (2013). “FHWA Localized Bottleneck Program.” <http://ops.fhwa.dot.gov/bn/resources/case_studies/madison_wi.htm> (Accessed 6/9/2014)
• Maps, Google (2014). <https://www.google.com/maps/search/homewood+suites+near+Hilton+Cincinnati,+OH/@39.2885017,-84.399993,83m/data=!3m1!1e3?hl=en> (Accessed 6/30/2014).
• Maps, Google (2012). <https://www.google.com/maps/@39.288408,-84.399636,3a,75y,243.6h,66.31t/data=!3m4!1e1!3m2!1si7sOFQJVai_eF3v7k8u_LQ!2e0> (Accessed 6/30/2014).
• https://www.fhwa.dot.gov/policy/ohim/hs06/htm/nt5.htm
• http://www-nrd.nhtsa.dot.gov/Pubs/811741.pdf
• http://content.time.com/time/nation/article/0,8599,1909417,00.html
• http://www.academia.edu/2899596/Crashes_and_Effective_Safety_Factors_within_Interchanges_and_Ramps_on_Urban_Freeways_and_Highways
• http://www.fairfield.ca.gov/latest_news/displaynews.asp?NewsID=447
• http://www-nrd.nhtsa.dot.gov/Pubs/811552.pdf
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QuestionsQuestions27