Accelerating traffic microsimulations: A parallel discrete-event queue-based approach for speed and scale

摘要

We present FastTrans - a parallel, distributed-memory simulator for transportation networks that uses a queue-based event-driven approach to traffic microsimulation. Queue-based simulation models have been shown to be significantly faster than cellular-automata type approaches, sacrificing spatial granularity for speed, while preserving link and intersection dynamics with high fidelity. Significant advances over previous work include the size of the simulated network, support for dynamic responses to congestion and the absence of precomputed routes - all routing calculations are executed online. We present initial results from a scalability study using a real-world network from the North-East region of the United States comprising over 1.5 million network elements and over 25 million vehicular trips. Simulation of an entire day's worth of realistic vehicular itineraries involving approximately five billion simulated events executes in less than an hour of wall-clock time on a distributed computing cluster. Initial results suggest almost linear speed-ups with cluster size.