A conflictcongestion model for pedestrianvehicle mixed evacuation based on discrete particle swarm optimization algorithm
A simulation model based on temporalspatial conflict and congestion for pedestrianvehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub-group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrianvehicle conflict levels.
pedestrianvehicle mixed evacuation discrete particle swarm optimization algorithm simulation temporalspatial conflict temporalspatial congestion