Data-driven mathematical simulation analysis of emergency evacuation time in smart station's operations management

Area of Science:

• Urban Planning
• Civil Engineering
• Public Safety

Background:

• Subway stations, especially complex transfer hubs, face significant safety challenges during emergencies.
• Accurate assessment of evacuation times is crucial for mitigating risks and ensuring passenger safety.

Purpose of the Study:

• To establish a robust emergency evacuation time model for complex subway stations.
• To identify critical bottlenecks and inform effective emergency management strategies.

Main Methods:

• Developed a model incorporating passenger flow rate, facility parameters, and crowd density.
• Analyzed factors like walking distance, train size, and stair parameters.
• Validated the model using Pathfinder software, achieving a 5.4% relative error.

Main Results:

• The model accurately assesses evacuation times in complex subway environments.
• Identified key bottleneck points (gates, doors, stairs) impacting evacuation.
• Demonstrated good consistency between model predictions and simulation results.

Conclusions:

• The developed model provides practical insights for improving subway safety and efficiency.
• Recommends implementing emergency diversion and passenger flow control measures.
• Offers valuable guidance for large-scale evacuation simulations in metro systems.