基于背景场的粒子群优化多出口疏散策略

Multi-exit Evacuation Strategy Based on Particle Swarm Optimization with Background Field

针对复杂建筑人群疏散出口选择策略问题,本文着重考虑行人对综合最短距离的认知差异,引入距离因素和密度因素建立混合距离策略,并结合修正的背景场建模规则,将出口选择策略融入到粒子群更新机理中,构建了基于背景场的粒子群优化算法的出口选择策略.通过数值实验模拟了出口选择策略的疏散性能,实验结果揭示了多出口建筑物内群体运动的机理,反映了疏散策略的动态化调整性能.仿真疏散过程也验证了多出口选择混合距离策略在群体疏散中的合理性和有效性.

In view of the crowd evacuation exit selection strategy question of complex buildings, this paper focuses on the cognitive difference of pedestrians in the synthetic shortest distance.The mixed distance strategy is established by introducing the distance factor and density factor, and combined with the modified background field modeling rules.The exit selection strategy is integrated into the particle swarm updating mechanism, and the exit selection strategy based on particle swarm optimization with background field is established.The evacuation performance of exit selection strategy is simulated by numerical experiments.The experimental results reveal the mechanism of group movement in multi-exit buildings, and reflect the dynamic adjustment performance of the evacuation strategy.The simulated evacuation process verifies the rationality and effectiveness of the multi-exit selection of the mixed distance strategy in group evacuation.