Pengshun, a Ph.D. student at the SRG, presented at the 2023 INFORMS Annual Meeting held on October 15-18, 2023, at the Phoenix Convention Center in Phoenix. His presentation was entitled “Spatial-queue Based Mesoscopic Traffic Model and its Applications in Wildfire Evacuation Simulations”.
To capture highly dynamic traffic situations, efficient mesoscopic models can deliver comprehensive yet fast results. Therefore, in this work, Bingyu and Pengshun developed a spatial-queue-based mesoscopic simulation model, with each vehicle represented as an autonomous agent with origin, destination, route choice, and other properties. Vehicles on the road are assumed to run at free-flow speed until joining a queue of vehicles at the downstream end. The length of the queue increases until no more vehicles can enter, creating the spillback effect often seen in congestion and disaster evacuation situations. Case studies are presented to demonstrate the applications in wildfire evacuations. The detailed disaggregated results are used to quantitatively evaluate intervention options and understand the challenges for evacuees in reaching safe destinations due to traffic bottlenecks and congestion.