Shortest path planning and dynamic rescue forces dispatching for urban flood disasters

Area of Science:

• Environmental Science
• Urban Planning
• Emergency Management

Background:

• Urban floods are increasing due to climate change and extreme weather.
• Floods threaten public safety, infrastructure, and economic development.

Purpose of the Study:

• To present a two-stage model for shortest path planning and dynamic dispatching of rescue forces during urban floods.
• To optimize emergency response by integrating path planning with rescue force allocation.

Main Methods:

• Developed a path selection model using a customized A* algorithm for worst-case travel times.
• Introduced a preference-based A* algorithm incorporating driver preferences.
• Created a bi-objective dynamic dispatch model using population density and real-time flood data.

Main Results:

• The model determines optimal paths for rescue vehicles considering worst-case travel times.
• Dynamic dispatching allocates rescue forces based on real-time demand and flood conditions.
• Integrated path planning and dispatching enhance emergency response efficiency.

Conclusions:

• The proposed two-stage model provides essential support for effective urban flood response operations.
• Optimized path planning and dynamic force allocation are crucial for mitigating flood impacts.