Path optimization for mass emergency evacuation based on an integrated model

The current study proposes an evacuation optimization model (IEO model) for mass emergency evacuation, which aims to minimize the average completion time, avoid traffic congestion, optimize the network utilization rate, and balance the exit loads. Pedestrians are divided into free evacuation pedestrians and organized evacuation pedestrians. The K-means algorithm and improved parameter adaptive DBSCAN algorithm are adopted to divide organized evacuation pedestrians into appropriate groups. Combined with an improved ant colony algorithm and the collision avoidance strategy, route scheduling for organized evacuation groups is carried out. A representative case is employed to benchmark the performance of the proposed model. The universality of the proposed model targeting different failure time of key exit and evacuation scale are analyzed. The developed model shows obvious advantages in mass evacuation compared with traditional statistical methods.

Automated summary

The current study proposes an evacuation optimization model (IEO model) for mass emergency evacuation, which aims to minimize completion time, avoid congestion, optimize network utilization rate, and balance exit loads. Pedestrians are divided into free evacuation pedestrians and organized evacuation pedestrians. The model incorporates algorithms to divide and schedule the organized evacuation groups. A representative case is used to benchmark the model's performance, and it shows advantages over traditional statistical methods in mass evacuation scenarios.