Improving a Regional-Scale Hurricane Evacuation Traffic Simulation Framework for Digital Twin Creation

Abstract

This study presents a hurricane evacuation traffic simulation framework for the New Orleans-Metairie Metropolitan area, aimed at creating a digital twin for hurricane evacuation planning and operation. The framework integrates signal timing plans and drivers’ hurricane evacuation route choice behavior into the simulation. Initially, the regional road network and local signal timing plans were refined to create a realistic traffic simulation environment. Locations with existing loop detectors along major evacuation routes in the real world with available data during the study period received more attention for result comparison purposes. Subsequently, this study explored a set of scenarios with respect to route choices and the percentage of informed drivers to determine the best parameter set that describes the actual route choices of drivers by comparing simulated traffic with observed traffic during Hurricane Ida (2021). A common observation from all simulation outputs indicated that the evacuation traffic peak occurred around 22 h before the storm landfall. The route choice behavior scenario testing results suggest that a stochastic shortest path model, which minimizes travel time and assumes 70% of drivers are informed, best matches the actual traffic observed at the selected locations during Hurricane Ida. This finding implies that over half of the drivers are aware of travel conditions and prioritize travel time during the evacuation. The simulation results highlight the significance of accurately representing real-world conditions, accounting for drivers’ evacuation route choices, and enhancing simulation outputs by incorporating real-time background traffic loading.