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行人动力学建模的关键是对行人运动方向和速度的选择进行描述.本文构建了基于多层有限状态自动机的行人Agent适应性决策模型；在此基础上，针对行人运动过程中快速决策的特征，通过构建基于认知启发式规则的行人运动行为规则集合，建立了描述行人微观运动行为的动力学模型.通过设计仿真实验并收集数据，对模型的有效性进行了验证.研究结果表明：模拟得到的行人交通流密度-速度关系与实测数据具有较好的一致性，流率-密度关系符合理论计算结果，基本图较好地符合实际观测的行人宏观交通流关系，认为本文提出的行人动力学模型具有交通上的合理性.

Cognitive Heuristics for Modeling Pedestrian Walking Behavior

The challenging issue in pedestrian crowd dynamics modeling is how to tackle the selection mechanism for pedestrian walking direction and step size.Based on hierarchical finite state machines,adaptive decision model for pedestrian agent walking behavior decision making is proposed in this paper.Furthermore,to reveal the characteristics of pedestrian decision-making in pedestrian motion,a set of rules based on cognitive heuristics is formulated to model the pedestrian crowd dynamics.Through designing computational experiments,the simulation data is collected to calibrate and validate the models.The study results show that the pedestrian flow density-velocity diagram is qualitatively consistent with the field data and flow rate-density diagram is dovetail into the reported results in the cited works.The proposed pedestrian crowd dynamics is reasonable to describe the pedestrian traffic pattern.