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Trip-Based Model for City-Scale Traffic Simulation: A Case Study on San Francisco
Time: 2019-07-31 15:30:00    From:


Academic Report on July.31,2019(3)

Reporter Topic:Trip-Based Model for City-Scale Traffic Simulation: A Case Study on San Francisco

ReporterDr. Bingyu Zhao, University of California, Berkeley

Time:15:30, July.31, 2019

Location:Conference Room 8319, Department of Engineering


     Traffic simulation is a powerful tool to understand the performance of the transportation system under various normal operation and disaster evacuation scenarios. In the first part of this talk, I will present a trip-based city-scale traffic simulation built for the city of San Francisco. The model features a detailed road network obtained from the OpenStreetMap and hour-long simulation time step to capture realistic variations in traffic conditions. The travel demand data are inferred from the Uber/Lyft pickup and drop-off counts published by the local transportation authorities. Traffic speed variations due to vehicle interactions are determined according to a simplified volume-delay macroscopic relationship, which is more efficient than applying microscopic rules (e.g., car following)   for evaluating city-scale traffic conditions. Preliminary validation of the results is conducted by comparing its results with a published model. Overall, the simulation has been demonstrated to run efficiently and produce reliable results. Then in the second part of this talk, a few ongoing projects based on the above traffic simulation tool will be presented, including applications in disaster evacuation, multi-infrastructure interaction and emission/pollution evaluation. The city-scale traffic simulation, together with its planned future improvements, is expected to greatly facilitate the policy testing and operational/emergency planning efforts on urban developments.