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Implementation of theMDSS Pooled Fund Study

David Huft, South Dakota DOTAASHTO Research Advisory Committee

Kansas City, MO July 27, 2010

Implementation of theMDSS Pooled Fund Study

David Huft, South Dakota DOTAASHTO Research Advisory Committee

Kansas City, MO July 27, 2010

Connecting South Dakota and the Nation

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Motivation for Maintenance Decision Support System (MDSS)

Motivation for Maintenance Decision Support System (MDSS)

Rising demands of travelers & commercial carriers High labor, material, equipment & fuel costs Constrained agency funding and staffing Reliable, timely condition reports hard to get Some weather conditions difficult to forecast Complex pavement response to weather and

maintenance New deicing chemicals available Environmental concerns about deicer use Retiring maintenance staff replaced by less

experienced workers

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MDSS Operating PremiseMDSS Operating Premise

If you know… road characteristics current conditions predicted weather physics & chemistry of

snow, ice, chemicals available resources

(material, equipment, schedule)

MDSS can recommend… treatment type application rate optimal timing

…and predict future road conditions

with or without treatments

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MDSS is New…but Not UnprovenMDSS is New…but Not Unproven

2002

2003

2004

2005

2006

Assess DOT Needs, Readiness

Evaluate FHWA Functional Prototype

Develop MDSS Software

6-State Limited Deployment

Refine MDSS Software

Validation Studies

8-State Field Trials

Broad Deployment

2007 Expanded Deployment

Independent B/C Analysis2008

10-State Field Trials

12-State Field Trials

14-State Field Trials

2009

2010

Refinement, Management Tools

2001

2000 Surface Transportation Weather Decision Support Requirements (FHWA)

FHWA Functional Prototype (by NCAR)

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MDSS Growth 2002-2010MDSS Growth 2002-2010

5 states(2002)

15 states(2010)

Meridian EnvironmentalTechnology

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Essential Elements of MDSSEssential Elements of MDSS Report actual road conditions Report maintenance

treatments Assess past & present

weather conditions Assess present roadway

state Predict storm weather Recognize resource

constraints Identify feasible maintenance

treatments

Predict road surface behavior

Communicate recommendations to supervisors and workers

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Achievements:Road Surface ModelingAchievements:Road Surface Modeling

MDSS considers past, current, and future conditions & actions

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Achievements:Road Condition PredictionAchievements:Road Condition Prediction

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Achievements: Information Integration & VisualizationAchievements: Information Integration & Visualization

Science-based integration of:– Weather observations– Weather forecasts– Maintenance vehicles– Human-reported

conditions & activities

GIS-based user interface for visualization and analysis of:– Weather observations &

forecasts– Road condition forecasts– RWIS/ESS data– Camera imagery– Mobile data & cameras– Blowing snow forecasts– Maintenance

recommendations & outcomes

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Achievements:Maintenance Plans & Outcomes

Achievements:Maintenance Plans & Outcomes

Different conditions forecast from different maintenance plans

Side-by-side comparisons permitted

Multiple maintenance plans and expected outcomes:– “Dynamic” approach to

maintain service level in consideration of cost, available resources

– “Standard” approach based on local, state, or national rules of practice

– “What If?” approach for user-defined plans

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Achievements:MDSS Field Trials 2008-2009Achievements:MDSS Field Trials 2008-2009

CA 66

CO 108108

IN 156156

IA 6565

KS 1818

KY 55

MN 185185

NENE 101101

NHNH 77

NYNY 1717

NDND 7777

SDSD 8080

VAVA 99

WYWY 6868

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Achievements:Field Decision SupportAchievements:Field Decision Support

Real-time data from maintenance vehicles– Road temperature– Air temperature– Observed precipitation– Observed road

conditions– Plowing activity– Chemical type & rate

MDSS adjusts predicted conditions and need for further maintenance

Real-time, vehicle-specific information fed back into vehicles– Radar imagery– Weather forecasts– Maintenance

recommendations– Fleet depictions

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Achievements:Field Decision SupportAchievements:Field Decision Support

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Mobile Data Collection Sensors & AntennasMobile Data Collection Sensors & Antennas

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Achievements:Training & EvaluationAchievements:Training & Evaluation

“Storm playback” of recent or saved storms at user-defined pace– Evaluation of

maintenance operations– What information was

available for decisions and when

– Train new employees on winter maintenance concepts and use of MDSS

– Predict effects of programmatic changes

Support emergency and traffic management

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MDSS Benefits:Predicted & RealizedMDSS Benefits:Predicted & Realized

Predicted Same level of service with

less cost– 23% material savings in

New Hampshire study

Achieve better level of service at same cost– 10-15% less

“unacceptable” conditions in New Hampshire study

8:1 Benefit/Cost Ratio New Hampshire

Similar studies performed in MN, CO

Only salt costs considered

Realized Indiana first-year statewide

deployment 2008/2009– $12M saved salt use

– $1.3M saved overtime/fuel

– $11M (of $40M) saved overall after normalizing for winter conditions

Mitchell Region (SD) event $60/mile versus $300/mile

Minnesota estimate ~50% material saved at defined level of service

More consistent winter maintenance

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Resistance to ChangeResistance to Change

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Change Obstacles & AgentsChange Obstacles & Agents

Obstacles Fear Technology glitches Cost Perceived value Executive support Conservative culture

Agents Training Maturing technology B/C analysis Actual success Targeted outreach Leadership &

implementation teams

“There are two basic rules of life: Change is inevitable and everybody resists change”

Roger Von Oech

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Pooled FundStudy MDSSProgression

Innovation

Envision

DesignBuild

Demonstration

Test

EvaluateRefine

Operation

Implement

EnhanceExpand

MDSS PFSImplementation ModelMDSS PFSImplementation Model

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MDSS Marketing EffortsMDSS Marketing EffortsGeneral MDSS FHWA Market-Ready

Technology AASHTO Technology

Implementation Group – Outreach brochure– 6½ minute video– Case studies– State & region meetings

AASHTO/FHWA/LTAPProduct Demonstration Showcases

National Center for Atmospheric Research

MDSS Pooled Fund PFS technical panel

meetings (3/year) MDSS PFS Fact

Sheet Segment of Product

Demonstration Showcase (by vendor and PFS states)

TRB conferences ITS America WASHTO, SCOH American

Meteorological Society

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Product Demonstration ShowcasesProduct Demonstration Showcases

Jointly sponsored by AASHTO TIG, FHWA Resource Center, FHWA LTAP

Free workshop State & local

participants State, local & vendor

presentations and demonstrations

Q/A panel discussions

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MDSS Pooled Fund Study: Lessons LearnedMDSS Pooled Fund Study: Lessons Learned

Winter maintenance is complex MDSS requires & drives culture change Implementation process is long Training is crucial to adoption & acceptance MDSS technology is still young and will

continue to mature MDSS does not replace the decision maker Benefits of MDSS as an information and

management tool may parallel direct benefits from recommendations

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MDSS Pooled Fund Study: Current Technical DirectionsMDSS Pooled Fund Study: Current Technical Directions

Foster initial deployments Evaluate, validate predictive capabilities Refine physical models More effectively use mobile data collection Link to other DOT systems

– Maintenance Management– Asset Management– Traveler Information

More powerful management tools & reports

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MDSS Pooled Fund Study: Benefits of MembershipMDSS Pooled Fund Study: Benefits of Membership Jointly directed

leading-edge R&D Convenient funding

mechanism Low-risk opportunity

to deploy Learning

– State to State– Vendor to State– State to Vendor

Intellectualproperty: open but not public domain

Nationally prominent forum for advancing MDSS and related technologies

New States Are Welcome

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Questions?Questions?

Thanks to: Tony McClelland

Indiana DOT Ben Hershey

Meridian Environmental Technology

For additional info:

David Huft

SDDOT Research Program Manager

605.773.3358

dave.huft@state.sd.us