| 城市轨道交通故障下客流分布计算及评估方法 |
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| 引用本文： | 刘峰博,周庭梁,王小敏.城市轨道交通故障下客流分布计算及评估方法[J].西南交通大学学报,2021,56(5):921-927, 966. |
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| 作者姓名： | 刘峰博 周庭梁 王小敏 |
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| 基金项目： | 四川省科技计划项目（2019YFH0097，2020YFG0353） |
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| 摘 要： | 为了精细化掌握城市轨道交通故障对乘客出行的影响，对等车、上车和下车过程的客流与列车交互状态进行抽象，建立了站台等待乘客、车内乘客等客流分布数据的计算方法，设计了动态客流仿真算法及乘客服务水平评估指标. 以实际线路为背景，以正常运营场景为参照，计算和评估了故障场景下的客流时空分布，分析了乘客等待时间对列车和站台上客流分布及出行时间的影响. 算例结果表明:具体故障下乘客多等待能通过避免离开而减少部分出行时间，但与正常场景相比，列车满载率高、站台人数多的现象增多；最大等待时间15 min与9 min相比，离开人数减少77.0%，带惩罚的总旅行时间降低超过10.0%，留乘发生率一样，但最大留乘人数增加94.1%，最大等待人数增加29.6%.
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| 关 键 词： | 城市轨道交通 客流分布 交互过程模型 仿真 故障 |
| 收稿时间： | 2020-09-07 |
Calculation and Evaluation Method of Passenger Flow Distribution under Urban Rail Transit Failure |
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| LIU Fengbo,ZHOU Tingliang,WANG Xiaomin.Calculation and Evaluation Method of Passenger Flow Distribution under Urban Rail Transit Failure[J].Journal of Southwest Jiaotong University,2021,56(5):921-927, 966. |
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| Authors: | LIU Fengbo ZHOU Tingliang WANG Xiaomin |
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| Abstract: | In order to accurately obtain the impact of urban rail transit failures on passenger travel, the interaction states between passenger flow and train are modeled for passengers’ waiting, boarding and alighting processes. A calculation method is established for passenger flow distribution such as waiting passengers on platforms and passengers in carriages. The dynamic passenger flow simulation algorithm and evaluation indexes of passenger service level are designed. Taking an actual rail line under normal operation scenario as the reference, the space-time distribution of passenger flow under urban rail transit failure is computed and evaluated. The effect of waiting time on passenger flow distribution on platforms and in carriages and the effect of waiting time on passenger travel time are analyzed. The case study shows that, passengers wait a little longer on the platform instead of leaving, which will reduce part of travel time under the specific failure. However, the situations of high load rate in carriage and large passenger volume on platform increases, compared with the normal scenario. With the maximum waiting time increasing from 9 min to 15 min, the number of departing passengers decreases by 77.0%, the total travel time with penalty decreases by more than 10.0%, and the passenger retention rate is the same, but the maximum numbers of stranded passengers and waiting passengers increase by 94.1% and 29.6%, respectively. |
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