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杨志强, 李俊铖, 史丰收, 何建涛. 城轨列车延误情况下受影响乘客出行选择建模[J]. 铁路计算机应用, 2020, 29(3): 60-64.
引用本文: 杨志强, 李俊铖, 史丰收, 何建涛. 城轨列车延误情况下受影响乘客出行选择建模[J]. 铁路计算机应用, 2020, 29(3): 60-64.
YANG Zhiqiang, LI Juncheng, SHI Fengshou, HE Jiantao. Modeling of passenger travel choice affected by urban rail train delay[J]. Railway Computer Application, 2020, 29(3): 60-64.
Citation: YANG Zhiqiang, LI Juncheng, SHI Fengshou, HE Jiantao. Modeling of passenger travel choice affected by urban rail train delay[J]. Railway Computer Application, 2020, 29(3): 60-64.

城轨列车延误情况下受影响乘客出行选择建模

Modeling of passenger travel choice affected by urban rail train delay

  • 摘要: 由于列车延误情况下接收到延误信息的乘客比例和有意愿改变出行方案的乘客比例等较难量化,导致无法掌握客流分布情况,采取的应急处理措施缺乏数据依据。为估算列车延误对网络客流分布的影响程度,分析了延误的传播机理,确定受延误影响的乘客数量、时空位置,研究其在接收到列车延误信息后的出行选择行为,基于多项Logit(MNL)模型构建延误情况下乘客出行方案选择模型,预判受影响客流在网络上的重分布并研发系统进行应用。实例证明,该模型能准确地估算受影响客流的重分布情况,对于列车延误类突发事件下的应急处置具有积极意义。

     

    Abstract: Because it is difficult to quantify the proportion of passengers who receive the delay information and the proportion of passengers who are willing to change the travel plan in case of train delay, the distribution of passenger flow cannot be mastered, and the emergency treatment measures taken lack of data basis. In order to estimate the impact of train delay on the distribution of network passenger flow, this paper analyzed the propagation mechanism of delay, determined the number and space-time position of passengers affected by delay, studied their travel choice behavior after receiving the information of train delay, built the model of passenger travel scheme choice under the condition of delay based on MNL model, predicts the redistribution of affected passenger flow on the network and developed the application system. The example shows that the model can accurately estimate the redistribution of the affected passenger flow, and it has positive significance for the emergency disposal of train delay emergencies.

     

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