基于快速通勤需求的地铁列车跨站停车方案优化  

Optimization of Skip-Stop Operation for Metro System Based on Rapid Commuting Demand

作　　者：江志彬[1,2] 王炳勋 李洪运 赵源 金晓琴 JIANG Zhibin;WANG Bingxun;LI Hongyun;ZHAO Yuan;JIN Xiaoqin(Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China;Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety,Tongji University,Shanghai 201804,China;Operation Dispatching Command Center of Shanghai Rail Transit Network,Shanghai Shentong Metro Group Co.,Ltd.,Shanghai 201100,China;Shanghai Tunnel Engineering&Rail Transit Design and Research Institute,Shanghai 200235,China)

机构地区：[1]同济大学道路与交通工程教育部重点实验室,上海201804 [2]同济大学上海市轨道交通结构耐久与系统安全重点实验室,上海201804 [3]上海申通地铁集团有限公司上海轨道交通路网运营调度指挥中心,上海201100 [4]上海市隧道工程轨道交通设计研究院,上海200235

出　　处：《同济大学学报(自然科学版)》2025年第3期410-419,共10页Journal of Tongji University:Natural Science

基　　金：国家自然科学基金(52372332);上海申通地铁集团合作项目(ST-TY019-2023);上海市隧道工程轨道交通设计研究院科研计划(Y202431)。

摘　　要：AB跨站停车方案可以满足高峰时段地铁通勤线路场景下的乘客快速出行需求。在充分考虑乘客换乘便利性和候车安全性的基础上,以最小化乘客总旅行时间并兼顾换乘乘客的公平性影响为目标,基于出行过程和换乘类别建立了地铁AB跨站停车0-1整数规划模型,并设计了高效的变邻域搜索算法,最后以上海地铁11号线为例验证了模型和算法的有效性。结果表明:变邻域搜索算法相较于遗传算法可在短时间内搜索得到较优解,能够很好地适用于AB跨站停车优化模型;AB跨站停车方案人均旅行时间可节省2.91 min,考虑人工经验策略的AB跨站停车方案人均旅行时间可节省2.12 min,且换乘乘客数量可减少41.18%;通过灵敏度分析可以得出,换乘站候车时间惩罚系数、列车始发间隔时间和最大AB类车站间隔是影响优化结果的关键因素。The AB skip-stop operation can meet the rapid travel demand of passengers in the scenario of commuting metro lines during peak hours.Considering passenger transfer convenience and waiting safety,a 0-1 integer programming model of AB skip-stop operation for the metro system was developed based on travel process and transfer type,to minimize the total travel time of passengers while considering the fairness of transfer passengers.Additionally,an efficient variable neighborhood search algorithm was designed to solve this model.Taking Shanghai Metro Line 11 as an example,the effectiveness of the model and algorithm was verified.The results show that the variable neighborhood search algorithm provides better solutions in a short time compared to the genetic algorithm and can be effectively applied to the optimization model of the AB skip-stop operation.Under the AB skip-stop operation,the average travel time of passengers is reduced by 2.91 minutes.When considering the artificial experience strategy under the AB skip-stop operation,the average travel time is reduced by 2.12 minutes,and the number of transfer passengers decreases by 41.18%.Sensitivity analysis reveals that the penalty coefficient for transfer station waiting time,train departure interval,and maximum AB station interval are the key factors affecting the optimization results.

关 键 词：城市轨道交通 列车停站方案 0-1整数规划 变邻域搜索算法 快速通勤需求 AB跨站停车 

分 类 号：U293.5[交通运输工程—交通运输规划与管理] U121[交通运输工程—道路与铁道工程]