An Agent-based Transit Signal Priority Simulation Model Using Bus Health Data (WIP)

摘要

Transit Signal Priority (TSP) is regarded as one of the efficient ways to improve public transit travel time delay and enhance operation, which involves the coordination among transit vehicle detection systems, TSP request servers, traffic control systems, and communication systems. Traffic simulations are usually conducted before deploying a new TSP system in the field to evaluate the impact of the deployment. This paper presents an agent-based model specifically for TSP simulation in a highly traffic congested area. The proposed model aims at shedding light on how to develop an agent-based discrete-event TSP simulation model using inputs extracted from event-driven bus health data in a highly congested area with a high volume of both vehicle and pedestrian traffic on a street with two-way bus traffic on M15 route in Downtown Manhattan, New York City.