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Dynamic Traffic Assignment and Applications in the Twin Cities Area Steve Wilson SRF Consulting Group SRF Consulting Group Duluth, Minnesota August, 2008.

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Presentation on theme: "Dynamic Traffic Assignment and Applications in the Twin Cities Area Steve Wilson SRF Consulting Group SRF Consulting Group Duluth, Minnesota August, 2008."— Presentation transcript:

1 Dynamic Traffic Assignment and Applications in the Twin Cities Area Steve Wilson SRF Consulting Group SRF Consulting Group Duluth, Minnesota August, 2008

2 Outline Background/FHWA Support Background/FHWA Support 35W Bridge Project 35W Bridge Project Test Applications Test Applications FHWA DTA Ongoing Development FHWA DTA Ongoing Development

3 What is Dynamic Traffic Assignment (DTA)? Mesoscopic traffic assignment model Mesoscopic traffic assignment model –More responsive to operational factors (queuing) than traditional travel demand models –More responsive to system level factors (route-changing) than traditional operations models

4 Travel Demand Model Assignment Limitations Trips are instantaneously on all links between origin to destination (not time-dependent) Trips are instantaneously on all links between origin to destination (not time-dependent) Congestion delay does not adequately reflect bottlenecks (upstream or downstream) Congestion delay does not adequately reflect bottlenecks (upstream or downstream)

5 DTA Models Availability Federal Highways DTA Federal Highways DTA Commercial Vendors Commercial Vendors –CITILABS –TRANSCAD –PTV –EMME/2 –Others

6 FHWA DTA (TrEPS) Program Started in 1995 Started in 1995 Two parallel tracks (Real-time ITS and Operational Planning) Two parallel tracks (Real-time ITS and Operational Planning) Linking planning and operations Linking planning and operations –Concept of Operational Planning Fill in the traffic analysis tool gap Fill in the traffic analysis tool gap –Macroscopic (static, regional) –Mesoscopic (dynamic, regional) –Microscopic (dynamic, corridor) Integration with TDM and microscopic model Integration with TDM and microscopic model

7 Program Activities DTA concept education and outreach DTA concept education and outreach –Webinars (online) – several per year –Short seminar (0.5-1 day) – on demand –Workshops (2.5 day) – 2 to 3 per year Mn/DOT (September 2008)

8 Program Activities Technical support to state agencies Technical support to state agencies –MPO/DOT – FHWA division – Resource center – FHWA HQ or TFHRC –Educational Support Training for DTA concepts Training for DTA concepts –Modeling Support Assist in initial modeling and dataset buildup Assist in initial modeling and dataset buildup Can be extended to consultants for a federally funded project Can be extended to consultants for a federally funded project Matching-fund may be needed if more involvement is requested Matching-fund may be needed if more involvement is requested

9 M&O Status (updated May 2008) State Users Workshops held Future Workshops (TBD)

10 Initial Development of Twin Cities FHWA DTA Model I-35W Bridge Collapse I-35W Bridge Collapse FHWA Response FHWA Response Pace of Study Pace of Study

11 MnDOT Model Development Importing of regional TDF model network Importing of regional TDF model network Importing of regional TDF model trip tables Importing of regional TDF model trip tables Network cleaning Network cleaning Simplified traffic control assumptions Simplified traffic control assumptions

12 MnDOT Model Development Calibration/adjustment of O-D matrices Calibration/adjustment of O-D matrices Testing of routing/improvement scenarios Testing of routing/improvement scenarios

13 Initial Development of Twin Cities FHWA DTA Model I-35W Bridge Collapse I-35W Bridge Collapse FHWA Response FHWA Response Pace of Study Pace of Study

14 I-35W UPA Project UPA Program Competition UPA Program Competition Innovative, multi- modal, priced Innovative, multi- modal, priced Open by end of 2009 Open by end of 2009

15 I-35W UPA Project Priced dynamic shoulder lane segment Addition of a HOT lane in Crosstown reconstruction project Conversion of existing HOV lane to HOT lane Also: BRT advanced implementation, park-ride, ITS

16 Why Dynamic Traffic Assignment? Availability Availability Better MOEs for comparison of Alternatives Better MOEs for comparison of Alternatives High-level operational evaluation High-level operational evaluation HOT lane capabilities HOT lane capabilities

17 Why Not Dynamic Traffic Assignment? Availability/readiness Availability/readiness Memory/CPU resources Memory/CPU resources Learning curve Learning curve Traffic engineers comfort zone Traffic engineers comfort zone

18 Analysis (Top 20 O-D pairs impacted by bridge collapse)

19 Twin Cities FHWA DTA Model

20 Travel time into Downtown area

21 FHWA DTA Model (Subarea)

22 Learning Curve CORSIM-like CORSIM-like Wiki help system Wiki help system Model Integration w/ TDF softwares Model Integration w/ TDF softwares

23 FHWA DTA HOT Lane Options Distance-based Distance-based Link-based Link-based Zone-based (coming soon) Zone-based (coming soon)

24 FHWA DTA HOT Lane Options Flexibility

25 Multiple User Class Flexibility

26 Flexible Traffic Flow Model

27 Exportable Tabular Output

28 Graphic Output

29 Time Stream Comparisons

30 FHWA DTA Tests (with subarea model) Sensitivity to geometric changes Sensitivity to geometric changes –Through lane add –Auxiliary lane add –Bottleneck queuing Stadium event departure Stadium event departure Peak-segment ramp O-D volumes Peak-segment ramp O-D volumes

31 Best Candidate DTA Uses Evacuation Planning Work zones Systems Planning Value pricing/HOT Lanes Benefit-Cost Analysis Travel demand model feedback

32 Lessons Learned New DTA model not short-term response New DTA model not short-term response Integration with planning/simulation models Integration with planning/simulation models Role of DTA in project development process Role of DTA in project development process

33 FHWA DTA V2.0 Modeling Features Lane-group based Anisotropic Mesoscopic Simulation (AMS) models Lane-group based Anisotropic Mesoscopic Simulation (AMS) models Relative gap gradient based assignment algorithm Relative gap gradient based assignment algorithm Epoch implementation for 24-hour to multi-day assignment Epoch implementation for 24-hour to multi-day assignment Destination and origin-based time-dependent least- cost path algorithms for various applications Destination and origin-based time-dependent least- cost path algorithms for various applications Vertical integration with TDM and VISSIM Vertical integration with TDM and VISSIM

34 2008 Projects and Applications Outlook In progress In progress –Military Deployment Transportation Improvement in Guam (PB, FHWA) –Interstate highway corridor improvement (TTI, TxDOT, ELPMPO) –Value Pricing (ORNL, FHWA; SRF, Mn/DOT, TTI, TxDOT) –Evacuation operational planning (UA, ADOT; LSU, LDOT; Noblis, FHWA; U of Toronto) –Integrated Corridor Management modeling (CS, FHWA) –Bay area regional modeling (CS, MTC) –Florida turnpike system traffic and evacuation analysis (FDOT Turnpike) –Commercial development traffic improvement (PAG)

35 Future Outreach Activities Arizona Arizona –Workshop (July 29-31, jointly funded by MAG and FHWA) Minnesota Minnesota –Mn/DOT workshop (September 09) California California –CalTrans and CA MPOs (August 11-13, 2008) 2-3 Kick-the-Tire webinars (FY 09) 2-3 Kick-the-Tire webinars (FY 09) 2-3 Training workshops (FY 09) 2-3 Training workshops (FY 09)

36 FHWA DTA V2.0 Modeling Features Suite of supporting tools to facilitate model use: Suite of supporting tools to facilitate model use: –Pre-processing Network cleaning Network cleaning Demand integration Demand integration –Post-processing Time-space diagrams Time-space diagrams Time-varying link statistics reports Time-varying link statistics reports Cumulative arrival curves Cumulative arrival curves Impacted vehicle analysis Impacted vehicle analysis Vehicle path analysis Vehicle path analysis

37 Acknowledgements FHWA FHWA –Jim McCarthy –Chung Tran Mn/DOT Planning Division Mn/DOT Planning Division –Brian Isaacson –Mark Filipi –Tony Fischer DynusT Labs DynusT Labs –Yi-Chang Chiu, University of Arizona

38 Questions? Steve Wilson


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