1. Modeling Drivers’ Route Choice Behavior, and Traffic Estimation and Prediction Byungkyu Brian Park, Ph.D. Center for Transportation Studies University of Virginia DriveSense14 Workshop, Norfolk, VA

2. Drivers’ Route Choice Model Existing literature – Considers disaggregate information but ends up with an aggregate model Can we consider a model for each driver? – Seems feasible with connected vehicle and smart phones and driver’s opt-in

3. Traffic Estimation & Prediction Estimates existing network condition using probe vehicles Estimates origin destination matrices for next 15-30 minutes Predicts future traffic conditions by assigning the OD matrices Evaluates multiple operational strategies and recommends best strategy

4. Motivation Weather vs. Route Guidance

5. Connected Vehicle Technology Wireless communications among vehicles and infrastructure

6. Questions on the Route Guidance 6  Will connected vehicle technology improve the quality of route guidance?  What happens if multiple route guidance strategies were implemented? Will they cancel-off benefits?

7. Route Guidance System Assumptions – Every equipped vehicle provides its origin-destination information (opt-in) – No Communications Loss Perfect communications V-2-I and V-2-V – On-Board Equipment (OBE or OBU) Vehicles Act as probe vehicles

8. Route Guidance System Assumptions (cont’d) – Guided Drivers Time varying traffic assignment A link-weighted K-Shortest Path algorithm to create reasonable path alternatives Time dependant minimum travel time path – Unguided Drivers Static assignment Fixed shortest distance path

9. Microscopic Traffic Simulation Model - VISSIM Microscopic, Time-step based simulation model Simulate traffic operations in urban streets and freeways Emphasize multi-modal transportations (Bus, LRT, Heavy Rail, etc.) OverviewOverview

10. Microscopic Traffic Simulation Model – VISSIM (cont’d) Traffic Flow Model Signal Control Model

11. Microscopic Traffic Simulation Model – VISSIM (cont’d) Various measures of effectiveness (e.g., delay, travel time, queue length, etc.) 2D & 3D animations OutputOutput

12. Route Guidance Strategies Guidance StrategyAcronymMajor Information from VII Latest Travel time -based Guidance LTG The latest link travel time Averaged Travel time -based Guidance ATG The average of link travel times Routing Travel time -based Guidance RTG Individual vehicles’ travel times of directional movements Predicted Travel time -based Guidance PTG Individual vehicles’ origin- destination tables

13. 13 Travel time of directional movements at an intersection Gathers all individual directional travel time through individual vehicles’ trajectory Routing Travel time-based Guidance (RTG)

14. Predicted Travel Time-Based Guidance (PTG) Based on DynaMIT program (i.e., Traffic Estimation and Prediction) Travel info (origin- destination) obtained from equipped vehicles

15. Route Guidance System Evaluation Simulation Test-Bed – Microscopic Traffic Simulator: VISSIM – A Hypothetical Urban Network 118 Road Segments including - a freeway - a major arterial 21 Signalized Intersections 9 All-Way-Stop Control 25 Origin/Destination

16. 16 Experimental Design Experimental factors and levels Experimental setup – Single operation : Total 2175 simulation runs and 1197 computer hours Single operation – Multiple operation : Total 150 simulation runs and 93 computer hours Multiple operation – Made 5 replications for each simulation

17. 17 Benefits of CV-based guidance strategies Single operation of guidance strategies Single operation Multiple operation of guidance strategies Multiple operation

18. 18 Benefits of individual strategies All guidance strategies produced benefits – Single operation of guidance strategies Single operation – Multiple operation of guidance strategies Multiple operation

19. 19 Impact of Market Penetration Rate

20. Proposed Research Bundle drivers’ route choice behavior model and traffic estimation & prediction system How? – Develop each driver’s route choice behavior model and keep model parameters on his/her smartphone or cloud – Implement driver’s route choice behavior model in TrEP

21. Where Are We? Just completed IRB training! Developed survey questionnaire to understand drivers’ characteristics and their stated preferences Evaluate drivers’ route choice behavior using driving simulator