城市群轨道交通直通线路优化设置方法

Optimal setting method of rail transit through lines in urban agglomeration

为满足城市群范围内旅客直达出行需求,提出了以多层次轨道交通衔接为基础的直通线路规划方案,探讨了不同方案带来的客运系统增益效果。基于超网络理论构建了城市群超网络模型,量化了旅客超路径的广义出行费用。构建了直通线路最优选择方案的双层规划模型:上层规划综合考虑运输商的利润和设置直通线路所节约的旅客出行成本;下层规划为城市群多方式交通系统的平衡分配模型,采用遗传算法和相继平均法求解上下层模型。最后,以京津冀城市群内衔接主要枢纽的客运线路为例对模型进行有效性验证,对直通线路设置规模的合理性进行论证。结果表明:在北京首都国际机场、北京站、北京西站、北京南站和天津站这5个枢纽之间,可开通备选直通线路11条,最佳直通线路编号为1、2、5、6、7、9;目前合理的直通线路规模为3条,开通之后的系统效益将提升28.03%,旅客平均出行时间降低10.02%。

To meet the demand of direct passenger travel within the scope of urban agglomeration,the through lines plans based on the connection of multi-level rail transit were proposed,and the gain effects of passenger transport system brought by different plans were discussed.The specific contents are as follows:a super network model of urban agglomerations multi-mode transportation was constructed based on the theory of hyper network.The generalized travel cost of passenger super path was quantified.A bi-level programming model for the optimal setting of through lines was constructed,in which the upper level programming considered the profit of the transporter and the saving of the passenger travel cost brought by the setting of through lines.The lower level programming was a balanced allocation model for the multimode transportation system of urban agglomeration.Genetic algorithm and successive average method were used to solve the upper and lower level models.Finally,the passenger lines connecting the main hubs in Beijing-Tianjin-Hebei Urban Agglomeration were taken as an example to illustrate the performance and applications of the model,and the rationality of the scale of the through line was demonstrated.The results show that,there are 11 alternatives through lines between Beijing Capital International Airport,Beijing railway station,Beijing West Railway Station,Beijing South Railway Station and Tianjin railway station.The best through lines are No.1,2,5,6,7and 9.The reasonable scale of the direct line is 3 at present.After opening,the system benefit will increase by 28.03%and the average travel time of passengers will reduce by 10.02%.