Population Evacuation in Motion: Harnessing Disaster Evolution for Effective Dynamic Emergency Response

This study introduces a robust Dynamic Population Evacuation (DPE) framework in response to the escalating challenges in wildfire-urban interface regions. The DPE model elevates emergency response strategies by seamlessly integrating traffic simulation, real-time mobility tracking, optimization systems leveraging advanced algorithms, and cloud-based communication. The offline component of the framework focuses on pre-disaster preparation by optimizing the allocation of evacuation shelters and generating initial route plans for impacted populations, incorporating changing on-the-ground hazard conditions and geography. The online phase dynamically reallocates shelters and provides real-time guidance for vehicle navigation. This approach significantly improves the efficiency and safety of evacuation processes by utilizing advanced algorithms and cloud infrastructure. Key innovations include an offline planning phase, optimizing shelter allocation and route plans with a keen eye on evolving hazards and geography. Extensive testing and simulations of the DPE framework, including models of real-world evacuation scenarios such as the Tubbs fire in California, validate the proposed approach and demonstrate significant improvement in efficiency, responsiveness, and safety for populations relative to traditional evacuation planning methods and frameworks. The study further underscores the broader applicability of the DPE model to enhance resilience and outcomes in urban evacuations not only for wildfires but also for other hazards such as floods and earthquakes.