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受停靠站特性、乘客上车行为及其分布特征等因素的影响，公共交通系统运行过程中容易产生集簇等复杂现象.本文细致考虑了停靠站在线路上和乘客在停靠站的分布情况，通过刻画乘客有序和无序的上车行为，构建了一个新的公交运输系统元胞自动机模型.数值模拟结果与解析结果高度吻合，清晰地刻画了车辆在公交线路上的时空分布，再现了公交运行中的堵塞和集簇现象，定量地评价了停靠站分布、乘客分布、不同上车模式对车辆平均速度的影响.本研究有助于进一步认识不同上车模式下集簇现象的形成机理，对规范上车行为和优化停靠站设计具有指导意义.

Modeling Passengers' Orderly and Disorderly Boarding Behavior in a Transit System

Cluster and other complex phenomena of bus flow easily occur due to such factors as bus stop location,passenger distribution and boarding behavior in a transit system.A new cellular automaton model which simultaneously considers these factors,particularly the passengers’ orderly and disorderly boarding behavior,is proposed in this paper.Numerical simulation results,which match the analytic results well,show that the model can explicitly depict the space-time trajectories of bus movement along a bus line,reproduce the cluster and jam phenomena of bus flow,and quantitatively evaluate the impacts of various factors on bus average speed.The study provides insights on formation mechanism of cluster phenomena under different boarding modes,advocates orderly boarding behavior and helps the optimization of locating bus stations.