Abstract
Abstract
For the stagnation problem that easily occurs in the process of simulating multi-floor and multi-staircase evacuation using a traditional social force model, in this paper, it is proposed to improve the social force model by introducing a moth-flame optimization algorithm, thus to establish a new evacuation model. The model firstly integrates the field model into a social force model as the pedestrian self-driving direction. Meanwhile, an objective optimization function of minimum system evacuation time is established based on the evaluation indexes, such as staircase congestion degree and average velocity, and the moth-flame optimization algorithm is improved by introducing dynamic inertia weight and random reverse learning strategy, thus establishing an evacuation optimization method. Finally, a simulation and numerical analysis is carried out for the multi-floor evacuation process using the experimental simulation platform built, which deeply analyzes the key factors influencing the model, gives the change relationships among the parameters such as evacuation time, initial pedestrian velocity, the number of pedestrians and staircase width, and verifies the effectiveness of the model.
Funder
the National Natural Science Foundation of China Grant No.
the Natural Science Foundation of Sichuan Province of China Grant No
the Innovation Team of Chengdu Normal University under Grant No.
Scientific Research Fund of Key Laboratory of Multidimensional Data Sensing and Intelligent Information Processing of Dazhou Key Laboratory under Grant No
Subject
Condensed Matter Physics,Mathematical Physics,Atomic and Molecular Physics, and Optics