A Meso-Scale Petri Net Model to Simulate a Massive Evacuation along the Highway System

Qabaja, Hamzeh; Ashqer, Mujahid I.; Bikdash, Marwan; Ashqar, Huthaifa I. · 2023 · Crossref

DOI: 10.3390/futuretransp3010019

archive: archived pipeline: cataloged verified

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Summary

This paper addresses the challenge of modeling traffic flow during massive evacuations caused by natural disasters, where infrastructure damage and unpredictable behavior render pre-planned strategies inadequate. The authors propose a mesoscopic simulation approach using a novel Colored Deterministic and Stochastic Petri Net (CDSPN) model. This method balances computational efficiency with the need to track individual vehicle dynamics, such as unique identifiers, speed, and assigned routes, without the excessive complexity of microscopic models or the lack of individual detail in macroscopic models. The primary motivation is to provide authorities with a tool that can simulate evacuation scenarios faster than real-time, allowing for the rapid evaluation of alternative plans and the identification of bottlenecks. The study implements the CDSPN model to simulate the evacuation of Guilford County, North Carolina. The model is automatically constructed from standard Geographic Information Systems (GIS) shapefiles, which define the highway system and assign addresses to the nearest safe targets, such as medical facilities or shelters. The simulation assumes evacuees obey traffic laws, with departure times following an exponential distribution (mean of 40 minutes) and routes determined by shortest-path algorithms. The resulting Petri net is substantial, comprising 35,476 places, 43,540 transitions, and 531,595 colored tokens, where each token represents a vehicle. The model incorporates specific assumptions, including that evacuees are at home when the order is issued, no background traffic exists, and individuals without vehicles converge at schools for public transit pickup. The simulation successfully modeled the dynamics of hundreds of thousands of vehicles moving through the highway system. The results indicated that the complete evacuation of Guilford County took approximately 8.7 hours. The model generated statistics and identified patterns of evaluation, such as congestion points, demonstrating its capability to analyze the evacuation process in reasonable detail. The authors note that the model meets several criteria for high-fidelity traffic simulation, including the ability to specify origin-destination zones, account for driver choices, and incorporate regional geographical areas. The significance of this work lies in providing a scalable, automated framework for emergency management. By leveraging GIS data to automatically generate complex Petri net models, the approach reduces data entry requirements and allows for the rapid testing of "what-if" scenarios. The mesoscopic nature of the model offers a practical compromise, capturing essential traffic dynamics like speed-density curves over large corridors while remaining computationally feasible for large-scale applications. This tool enables authorities to adapt to last-minute infrastructure information and optimize evacuation strategies, potentially reducing delays and improving safety during major disasters.

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• evacuation egress