基于分子动力学及多智能体的地铁车站行人仿真研究

项目名称： 基于分子动力学及多智能体的地铁车站行人仿真研究

项目编号： No.51278029

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 建筑科学

项目作者： 陈峰

作者单位： 北京交通大学

项目金额： 80万元

中文摘要： 地铁车站行人密度较高，行人之间会发生接触甚至挤压现象，离散微观行人仿真方法只能研究行人的运动，不能反映其受力，仿真达到的最大行人密度与实际有差距，不能很好地用于车站行人仿真。社会力模型从受力的角度研究行人运动规律，兼顾了行人运动状态和受力状态，能解决上述问题，但是该模型还存行人路径选择盲目、发生不必要的碰撞等问题。本研究拟针对这些问题，采取分子动力学相关方法，设计社会力模型的分子动力学算法，引入linked-list cell方法，编程实现社会力模型，提高社会力模型计算速度；基于多智能体思想，设计行人智能路径选择算法，克服社会力模型将行人等同于物理粒子的弊端；采用椭圆形模拟行人，并基于车站行人调研和测试，标定校核模型参数，得到更符合实际的仿真效果；最终开发仿真工具，并将其应用于车站设施布局的仿真评价。

中文关键词： 城市轨道交通；行人仿真；社会力模型；分子动力学；多智能体

英文摘要： The pedestrian density of metro station is relatively high, and pedestrian often touch or even squeeze each other. Discrete micro-simulation model only study the movement rather than the force of the pedestrian, and also the attained pedestrian density in these models is smaller than that in practice, so these models are not very applicable for metro station. The social force model studies the pedestrian movement from the view of force, taking both the movement and the force into account. Therefore it can solve the above problem. However, there are still some problems for this model. This research will focus on these problems. Firstly, with the molecular dynamic method, the computation algorithm will be designed, and the linked list cell method will be used to accelerate the computing speed. Secondly, the intelligent route choice algorithm will be formulated based on multi-agent theory to eliminate the disadvantage that pedestrians are considered as physical particles. Then the pedestrian will be simulated as ellipse and the model parameters will be calibrated and verified through pedestrian field study to reach more realistic results. Finally, a pedestrian simulation tool will be developed and will be applied in layout evaluation of metro station facilities.

英文关键词： Urban Rail Transit；Pedestrian Simulation；Social Force Model；Molecular Dynamics；Multi-Agent