1. METRO Dynamic Traffic Assignment in Action COST Presentation ODOT Region 4 April 1, 2014 1

2. METRO What is DTA? 2

3. METRO Topics / Agenda DTA Overview Case Study: Sunnybrook Extension Group discussion on experiences & desires 3

4. METRO Why DTA? More Realistic Than Static Assignment Models  Vehicle trajectories, queuing, density, etc.  Capacity constrained & granular time influence  Identify bottlenecks & diversion  Reflects daily variability  analyze reliability  Model events, such as train crossings, work zones, special events, and crashes 4

5. METRO Why DTA? Relatable Performance Measures  Travel time, speed and reliability rather than LOS, delay and v/c ratios  Direct benefit / cost  Can monetize $ time, reliability and safety exposure Less $ than Microsimulation  Import from GIS or existing model / Simplified operations 5

6. METRO Why Not DTA? Not a multi-modal analysis tool  Limited transit analysis; no ped/bike modes…can be exported to microsim Not an intersection analysis tool  Can be exported to Synchro or other deterministic model More time and data intensive than Regional Travel Demand Model  Less than microsimulation though… DTA tools are generally less established  Understand assumptions, defaults, and algorithm, e.g. queuing methods 6

7. METRO Good Project Candidates for DTA When diversion is key  Work Zones  Tolling/Congestion Pricing  Active Traffic Management – Non-Recurring Incidents  Crashes, At-Grade Railroad, Traveler Information, Ramp Metering  Safety Evaluation  Exposure based metrics When realistic capacity is key  Bottleneck Evaluations  queuing, delays  Alternatives Analysis – scenario benefit/cost evaluations  Signal Timing – route selection impacts, not optimization 7

8. METRO Sample List of DTA DynaMEQ DYNASMART-P DynusT DTALite Cube Avenue Transmodeler VISSIM & Paramics (DTA function) 8

9. METRO Sample of Key Differentiators between DTA Tools Run Time  DTA Lite = Minutes vs. Others = Hours  Accuracy vs. Data Needs Network Fidelity  Link vs. lane-based, intersection storage lanes? Network Size Capacity  Certain tools may be limited on the size of network they can run upon Ease of Use  “Polish” and features 9

10. 10 Data Hub Field Data Land Use, Safety & Emissions Models HCM & Signal Timing Models Micro- simulation Models Dynamic Traffic Assignment Models Travel Demand Forecasting Models AMS Data Hub Field Data Land Use, Safety & Emissions Models HCM & Signal Timing Models Micro- simulation Models Dynamic Traffic Assignment Models Travel Demand Forecasting Models FHWA: Data Hub Project with NEXTA & DTA Lite Current Practice Ad Hoc With AMS Data Hub Systematic

11. METRO DTA Lite Tools 11

12. METRO SUNNYBROOK EXTENSION DTA ALTERNATIVES ANALYSIS 12

13. METRO I- 205 Sunnyside Road Sunnybrook Road Harmony Road King Road Otty Road Monterey Avenue Causey Avenue Fuller Road SE 82 nd Avenue Hwy 224 Johnson Creek Blvd. Schumacher Road 13

14. METRO DTA: Corridors Analyzed 14

15. METRO DTA: Sunnybrook Extension 15

16. METRO DTA: Comparing Average Travel Times 16

17. METRO DTA: Freeway Average Travel Times 17

18. METRO DTA: Comparing Reliability 18

19. METRO DTA: Buffer Time in Minutes 19

20. METRO DTA: Speed Scans 20

21. METRO DTA: Cost/Benefit Analysis 21

22. METRO DTA: Cost/Benefit Analysis 22

23. METRO DTA: Lessons Learned Higher resolution elements needed for DTA (vs. Static)  Lane drops, storage, # and location of zones and connectors  Higher resolution trip tables needed  Don’t use a local street network Iterative calibration necessary  Volume and travel time in both time and space  Things change in future years…v/c > 1.0 doesn’t work well in DTA; Origin- Destination Matrix Estimation is an option Set realistic capacity assumptions in the model  Jam Density has a big impact  Signal Timing has a big impact  max cycle length? 23

24. METRO DTA Lite Jam Density Sensitivity Test Minutes & Miles Per Hour 24

25. METRO DTA Lite Import of Signal Timing Import Synchro into NEXTA (GUI for DTA Lite)  Processing required (node numbers, coordinates) 25

26. METRO Calibrate O-D Demand Matrices 26

27. METRO Group Discussion 27 Shaun Quayle; squayle@kittelson.com