摘要
针对复杂场景下的人群疏散运动,提出一种改进的社会力模型与人工蜂群算法相结合的方法.利用改进的人工蜂群算法进行实时宏观路径规划,底层结合修正的社会力模型指导个体运动.考虑到视角对个体运动的影响,在原始社会力模型基础上引入视觉影响因子,同时消除互不可见个体间的社会心理力;依据行人疏散过程中出现的结伴、从众现象,在人工蜂群算法中引入分组策略,同时将疏散时间作为适应度评判标准,符合现实疏散中行人的心理特征,提高了算法的收敛速度及寻优精度.实验结果表明,该方法下人群运动流畅自然,能够实现更真实的仿真效果,对紧急情况下的人群疏散具有指导意义.
Contrapose the crowd evacuation movement under complex scene, an improved method combine social force model with artificial bee colony algorithm is proposed. Using the improved artificial bee colony algorithm for real-time macro path planning, the underlying amendatory social force model to guide individual movement. Considering the influence of visual angle on the movement of individuals,introducing the visual impact factor based on the original social force model, at the same time, eliminating invisible indi- vidual＇s social psychological force between each other. According to the companion and conformity phenomenon appeared in pedestrian evacuation, introducing the grouping strategy to artificial bee colony algorithm, meanwhile, evacuation time is used as criterion of the fitness evaluation. It＇s in accord with the psychological characteristics of pedestrian evacuation in reality, and improves the algorithm convergence and optimization accuracy. The experimental result shows that with this method, the crowd movement is smooth and natural, can achieve a more real simulation effect, and has the guiding significance for the emergency evacuation.
出处
《小型微型计算机系统》
CSCD
北大核心
2016年第8期1725-1729,共5页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(61272094
61472232
61572299
61402269
61402270)资助
山东省自然科学基金项目(ZR2014FQ009)资助
山东省高等学校科技计划项目(J13LN13)资助
关键词
人群疏散
社会力模型
路径规划
人工蜂群算法
crowd evacuation
social force model
path planning
artificial bee colony algorithm
