SFLF: Social Forces Based Leader-Follower Emergency Evacuation Model

The simulation results of fire safety evacuation often deviate greatly from reality and have a low guiding effect on the evacuation of people. This paper, based on the social force model, introduces the leader-follower model and conducts in-depth research on the evacuation of people. It proposes the Social Forces Based Leader-Follower Emergency Evacuation Model, which is called the SFLF model. In the path planning of the SFLF model, the eACO (evacuation Ant Colony Optimization) algorithm is introduced, thereby constructing a complete SFLF model and realizing the Leader-Follower evacuation of people in various fire scenarios. Finally, the evacuation algorithms of the SFLF model, random algorithm, greedy algorithm, general Leader-Follower, and general eACO algorithm are compared in terms of the success rate of evacuation. The experiments prove that the average evacuation success rates of the random algorithm, greedy algorithm, general Leader-Follower, and general eACO algorithm are 42.2%, 59.4%, and 90.8% respectively, while the average evacuation rate of people based on the SFLF model is 95.6%, with the highest evacuation success rate and the best evacuation effect.