1. NTERFACING THE MORPC REGIONAL MODEL WITH DYNAMIC TRAFFIC SIMULATION INTERFACING THE MORPC REGIONAL MODEL WITH DYNAMIC TRAFFIC SIMULATION David Roden (AECOM) Supin Yoder (FHWA) Nick Gill and Zhuojun Jiang (MORPC) Rebekah Anderson and Greg Giaimo (ODOT) FHWA – TRANSIMS Deployment Project

2. Agenda  Study Overview  Network Conversion and Debugging  Trip and/or Tour Conversion  User Equilibrium Assignment and Convergence  Output Results and Sensitivity Tests MORPC TRANSIMS Implementation 2

3. Purpose of the Study  AECOM, MORPC, ODOT, and FHWA are participating in a study to route and simulate MORPC’s tour-based demand on a TRANSIMS network  Create a time-dependent TRANSIMS network  Route and simulate TP+ trips on the TRANSIMS network  Route and simulate MORPC tours on the TRANSIMS network  Feedback travel times from TRANSIMS to the tour model  Create a time-dependent transit network and tour routing MORPC TRANSIMS Implementation 3

4. Network Conversion Process MORPC TRANSIMS Implementation 4

5. TRANSIMS Network MORPC TRANSIMS Implementation 5

6. TRANSIMS Coding Concepts MORPC TRANSIMS Implementation 6

7. Original/Default TRANSIMS Network MORPC TRANSIMS Implementation 7

8. Zone Connector Activity Locations MORPC TRANSIMS Implementation 8

9. Freeway Access Problems MORPC TRANSIMS Implementation 9 Loop ramps were added to the TP+ network to improve results

10. TRANSIMS Travel Demand Concepts  TRANSIMS models individual persons for 24+ hours  Trips between specific activity locations, at specific times of day, using a specific travel mode and vehicle  Activity locations – street locations / block faces  Time of day (start/end/duration) – seconds  Modes – walk, bike, drive, ride, transit, P&R, K&R, etc.  Convert aggregate trip tables to individual travelers at specific locations and trip start times  Zones  activity locations within the zone  Daily/time period  second of the day MORPC TRANSIMS Implementation 10

11. Trip Table Conversion Process MORPC TRANSIMS Implementation 11 Diurnal Distributions MORPC Diurnals SmoothDataTP+ Scripts Trip Tables Activity Location ConvertTrips Trip File Population File Vehicle File Household File Activity Location Subzone Factors LocationData MORPC Zone DataNon-HH Trip TablesZone Boundaries MORPC HH-ToursBlock DataBlock BoundariesTraffic Counts

12. Diurnal Smoothing Results MORPC TRANSIMS Implementation 12

13. Activity Location Weights  Use subzone socio-economic data to calculate trip attraction weights by trip purpose and orientation for each activity location within a TAZ  MORPC/ODOT provided a block data file to calculate the attraction weights  Inconsistencies between the TAZ and block file boundaries and socio-economic attributes necessitated complex data processing MORPC TRANSIMS Implementation 13

14. TAZ – Block Data Integration Issues MORPC TRANSIMS Implementation 14

15. MORPC Tours  TRANSIMS Tours MORPC TRANSIMS Implementation 15 Activities have locations, start times and durations Trips connect activities

16. TRANSIMS Router and Microsimulator  Router builds a unique path for each trip  Between origin and destination activity locations (link-offset)  Starting at a specific second of the day  Using a specified travel mode and vehicle  Based on network travel times in15-minute increments  Microsimulator moves vehicles between link-lane-cells on a second-by-second basis  Cells are 6 meters long  Vehicles move 0, 1, 2, 3, 4, 5, or 6 cells each second Speeds = 0, 13.5, 27.0, 40.5, 54.0, 67.5 or 81.0 mph MORPC TRANSIMS Implementation 16

17. Microsimulator Feedback Loops MORPC TRANSIMS Implementation 17 Microsimulator NetworkTravel Paths Bottlenecks Travel Times Router Trips / Tours Change? Stop No Yes

18. Convergence Statistics  Convergence is defined using multiple statistics  Simulation stability and network performance Number and location of “lost” vehicles by time of day Difference between the average link delay and the Microsimulator link delay – vehicle hours of travel by link and time of day  User Equilibrium – no traveler can improve their travel time (impedance) by changing paths Difference between the simulated path and the minimum impedance path for each traveler – vehicle hours of travel by trip The percentage of travelers with significant differences MORPC TRANSIMS Implementation 18

19. Lost Vehicle Problems MORPC TRANSIMS Implementation 19 Iteration 1Iteration 25

20. Trip-Model Convergence Statistics MORPC TRANSIMS Implementation 20

21. Trip Gap by Time of Day MORPC TRANSIMS Implementation 21

22. Link VHT Gap by Time of Day MORPC TRANSIMS Implementation 22

23. ATR 601: I-70 at Brice Rd. MORPC TRANSIMS Implementation 23

24. Total Volume: All Stations MORPC TRANSIMS Implementation 24

25. Operational Impact Test  Used the turning movement volumes from the simulation to update the signal timing plans for all signals in the region  Applied Progression to calculate signal offsets  Applied Router-Microsimulator to convergence MORPC TRANSIMS Implementation 25

26. Signal Timing and Progression MORPC TRANSIMS Implementation 26 Aggregate Wait Time ProblemsSignal Progression Corridors

27. Daily Cycle Failures – Original MORPC TRANSIMS Implementation 27

28. Daily Cycle Failures – Operational Test MORPC TRANSIMS Implementation 28

29. Next Steps  Implement global iterations between the tour-model and the network simulation  Perform sensitivity tests and future forecasts  Refine operational details in downtown to provide demand data for a VISSIM subarea analysis  Upgrade the model to TRANSIMS Version 5 Studio and Visualizer MORPC TRANSIMS Implementation 29