A coupled lattice Boltzmann-cellular automata model for dynamic optimization of vehicle evacuation route during urban flooding

Urban flooding presents significant obstacles to sustainable urban development and water environment safety, demanding innovative solutions for effective disaster response. This research proposes a novel Cellular Automata Dynamic Evacuation Route Optimization (CA-DERO) that dynamically updates evacuation routes in real-time based on evolving flood conditions. The model integrates key factors such as hydrodynamic behaviors, topography, and vehicle responses under emergency scenarios. Using a suburban flood scenario as a case study, the CA-DERO framework demonstrates its capability to generate adaptive routing strategies that respond to changing road accessibility during flood progression. Specifically, the proposed optimization algorithm can plan dynamic evacuation routes under different anticipated response times: when [Formula: see text]<0, it provides emergency routes for unexpected flooding; at [Formula: see text]= 0, it identifies dynamically optimized shortest paths under current flood conditions; and for [Formula: see text], it generates safer evacuation paths considering future risks. Furthermore, the study extends to group simulations, where CA-DERO successfully captures congestion dynamics on high-traffic routes. These findings provide practical insights for policymakers and urban planners aiming to improve flood risk management and emergency response strategies.