Hurricane Evacuation

Hurricane evacuation research focuses on optimizing the efficiency and safety of evacuations, aiming to minimize casualties and economic losses. Current efforts utilize various machine learning models, including deep learning architectures like LSTM and GCNs, agent-based simulations to model human behavior and traffic flow, and optimization algorithms to improve resource allocation and scheduling. These advancements aim to improve real-time traffic prediction, optimize shelter allocation, and enhance building design for safer evacuations, ultimately leading to more effective disaster preparedness and response strategies. The integration of diverse data sources, such as connected vehicle data and social media, is also a key trend, improving the accuracy and timeliness of predictions.