Simulation Pipeline for Traffic Evacuation in Urban Areas and Emergency Traffic Management Policy Improvements through Case Studies

TL;DR

This paper develops a comprehensive traffic simulation pipeline to evaluate and improve evacuation strategies in urban areas during disasters, demonstrated through case studies in California involving wildfires.

Contribution

It introduces a versatile simulation framework that integrates map creation, demand modeling, vehicle behavior, and policy analysis for emergency evacuation planning.

Findings

Identified traffic bottlenecks during wildfire evacuations.

Proposed policy improvements to enhance evacuation efficiency.

Validated the pipeline with real-world case studies in California.

Abstract

Traffic evacuation plays a critical role in saving lives in devastating disasters such as hurricanes, wildfires, floods, earthquakes, etc. An ability to evaluate evacuation plans in advance for these rare events, including identifying traffic flow bottlenecks, improving traffic management policies, and understanding the robustness of the traffic management policy are critical for emergency management. Given the rareness of such events and the corresponding lack of real data, traffic simulation provides a flexible and versatile approach for such scenarios, and furthermore allows dynamic interaction with the simulated evacuation. In this paper, we build a traffic simulation pipeline to explore the above problems, covering many aspects of evacuation, including map creation, demand generation, vehicle behavior, bottleneck identification, traffic management policy improvement, and results analysis. We apply the pipeline to two case studies in California. The first is Paradise, which was destroyed by a large wildfire in 2018 and experienced catastrophic traffic jams during the evacuation. The second is Mill Valley, which has high risk of wildfire and potential traffic issues since the city is situated in a narrow valley.