EMME User’s Conference

1. EMME User’s Conference Project Experience of a DYNAMEQ Simulation Model : TRPC – Smart Corridors Project Natarajan JANA Janarthanan PhD, PTP Ming-Bang Shyu PhD, PTPFehr & Peers Jailyn Brown Thurston Regional Planning Council October 4, 2010

2. Outline Project Overview Model Development Model Validation and Calibration DYNAMEQ (DTA) Simulation VMT / Emission Calculation Q&A

3. Geography Area : 727 Sq Miles Population: 245,300 (2009) 373,000 (2030) Olympia is the capitol of Washington State Freeway: 90 Miles Arterials: 220 Miles Collectors: 360 Miles Source: Fehr and Peers (2009); courtesy map Google

4. Study Corridors

5. Why DTA Model? TRPC wants a tool to evaluate ITS and TSP options to calculate emissions to create a traffic operations model for its jurisdictions to integrate signal coordination efforts Traditional travel demand models have limitations Micro-simulation models for a larger area is not practical

6. What is Dynamic Traffic Assignment (DTA) Model? Time-dependent methodology Experienced shortest (minimal-cost) path from origin to destination in response to roadway connectivity, capacity, or travel demand changes.

7. Why DYNAMEQ DTA Model? A simulation-based approach capturing system dynamics (many are deterministic) Car following and Lane changing methodology Intersection controls

8. DYNAMEQ Model Development NETWORK Import network into DYNAMEQ from EMME Model Run DTA to check convergence and flow problems Refine network by adding missing intersections on the corridors Modify centroid connectors for the zones around two corridors to reflect field conditions Add intersection detail (geometry & turning pockets) Add signal data / intersection controls 81 signals & 67 stopped controls Network properties in DYNAMEQ model: – 800 centroids – 2500 regular nodes – 8000 links – 20 transit lines (study corridors only)

9. DYNAMEQ Model Development TRIP TABLES PM peak hour trip tables brought from Travel Demand Model 30-mimute Pre-peak and post-peak loading applied The modes are SOV, HOV & Truck

10. DYNAMEQ Model Development Travel Demand Model - Link node basis DTA Model - Lane basis

11. DYNAMEQ Model Development

12. DYNAMEQ Model Development • Assign trip tables in DTA model – without any intersection controls and validation / calibration • network check • Flow blockage check • Convergence check

13. DYNAMEQ Model Development Link Volume Comparison DYNAMEQ model without intersection controls and validation EMME’s Static assignment model

14. DYNAMEQ Model Development Run DTA with intersection controls without any validation / calibration

15. DYNAMEQ Model Development DTA without intersection controls DTA with intersection controls

16. DYNAMEQ Model Development General Approaches to Validate / Calibrate the models

17. Model Convergence

18. Base Year Model Validation / Calibration – Link Volume Including I-5 R Squared = 0.955, Slope = 1.01

19. Base Year Model Validation / Calibration – Link Volume Excluding I-5 R Squared = 0.894, Slope = 0.97

20. Base Year Model Validation / Calibration – Turn Movement R Squared = 0.900, Slope = 1.00

21. Comparison of Travel SpeedPM Peak Hour Weekday Observed Travel Speed (mph) DTA Model Travel Speed (mph)

22. Base Year Model Validation / Calibration – Travel Time Model Output Observed Travel Time

23. Base Year Model Simulation • Density Source: Movie clip from the DTA model simulation

24. Base Year Model Simulation • Outflow Source: Movie clip from the DTA model simulation

25. Base Year Model Simulation • Queuing Source: Movie clip from the DTA model simulation

26. Base Year Model Sensitivity Analysis using an Incident Scenario -Tested on I-5 SB in the vicinity with two-lane closure - Separated car and truck demands into two -- external-external trips -- others - Run 10 more iterations with incident lane closure.

27. Base Year Model Simulation • Incident Analysis – Paths Incident location Source: Snapshot from the DTA model simulation

28. Base Year Model Simulation • Incident Analysis – Flow change Incident location Source: Snapshot from the DTA model simulation

29. Base Year Model Simulation • Incident Analysis – Speed change Incident location Source: Snapshot from the DTA model simulation

30. Emission Calculation

31. Comparison of Speed Output EMME Model DYNAMEQ Model

32. Comparison of VMT EMME vs. DYNAMEQ

33. Comparison of PM10 Calculation

34. Emissions on Corridor

35. Benefits of DYNAMEQ Model • More realistic traffic simulation • - Lane based simulation • - Traffic congestion / queuing • - Intersection delays • Region-wide traffic operation model • Hot spot identification and problem solving • TSP analysis • Emission Calculation • Congested areas/network analysis

36. Data needs Network resolution Demand Adjustment Validation/Calibration Emissions Calculations Lessons Learned building this Dynameq Model Travel Demand Model DYNAMEQ Model Micro Traffic Simulation Model

37. Do you have any questions on this presentation or related issues? Jana / Ming Fehr & Peers11410 NE 122nd Way, Suite 320 | Kirkland, WA 98034425.820.0100 - T | 425.821.1750 – F jana@fehrandpeers.com m.shyu@fehrandpeers.com www.fehrandpeers.com