Abstract:

In order to facilitate the passenger assignment of urban rail transit network, a nonlinear discrete choice model, which is based on the discrete choice theory, is designed to formulate urban rail transit passengers’route choice behavior. In this study, the commuter flow and ordinary flow in urban rail transit are separately considered. On this basis, a SP survey is conducted in Beijing Subway, whose results are used to investigate the difference in preferences between different groups and calibrate model parameters. In order to ensure the accuracy of proposed model, the attributes of stations, trains and passengers are elaborated and a range of variables, such as waiting time, in-vehicle congestion degree and walking velocity, are included in the model. At last, an example urban rail transit line, in which trains in different speed are simultaneously operated, is used to validate the model and the result shows that most commuters have a long distance travel and do not mind the congestion, while ordinary passengers prefer local trains, for cozy trip and less interchange, which is consistent with the survey results.

Key words: urban traffic, route choice, discrete choice model, urban rail transit, SP data

摘要：

为解决成网条件下城市轨道交通的客流分配问题，引入随机效用理论，建立乘 客乘车路径非线性随机效用模型.通过北京地铁实地调查，将通勤者和休闲者区分开，研 究不同群体的乘车偏好，获取SP数据进行参数估计.为提高乘客行为预测精度，对三类影 响因素——车站特性、列车特性、乘客主体特性进行细致描述；为反映乘客个体的随机特 性，模型的乘客主体设定了候车时间、拥挤度、步行能力等变量.以典型轨道交通线路（线 路上快慢车共轨运营）为例验证模型有效性与先进性.结果显示，通勤者出行距离长且不 介意拥挤，休闲者偏好舒适少换乘路径，故多选择慢车，与调查的情况一致.

关键词: 为解决成网条件下城市轨道交通的客流分配问题, 引入随机效用理论, 建立乘 客乘车路径非线性随机效用模型.通过北京地铁实地调查, 将通勤者和休闲者区分开, 研 究不同群体的乘车偏好, 获取SP数据进行参数估计.为提高乘客行为预测精度, 对三类影 响因素——车站特性、列车特性、乘客主体特性进行细致描述；为反映乘客个体的随机特 性, 模型的乘客主体设定了候车时间、拥挤度、步行能力等变量.以典型轨道交通线路（线 路上快慢车共轨运营）为例验证模型有效性与先进性.结果显示, 通勤者出行距离长且不 介意拥挤, 休闲者偏好舒适少换乘路径, 故多选择慢车, 与调查的情况一致.