华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (8): 11-19.doi: 10.12141/j.issn.1000-565X.240362

• 智慧交通系统 • 上一篇    下一篇

城市轨道交通限流背景下的协作疏解研究

王豹  罗霞  乔璇  苏启明   

  1. 西南交通大学 交通运输与物流学院,四川 成都 611756
  • 出版日期:2025-08-25 发布日期:2025-01-17

Research on Collaborative Transferring Under the Condition of Urban Rail Transit Passenger Flow Control

WANG Bao  LUO Xia  QIAO Xuan  SU Qiming   

  1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, Sichuan, China
  • Online:2025-08-25 Published:2025-01-17

摘要:

针对现阶段对城市轨道交通网络限流场景下的被限制客流转运关注不足等问题,对特定限流条件下转运车辆线路布设和运力配置进行研究。首先,分析量化不同转运线路条件下,乘客选择乘坐转运车辆的效用和选择概率。在此基础上,以最小化总期望旅行时间,最小化转运车辆开行成本,最大化轨道交通网络拥堵区间客流疏解量为目标,构建了限流场景下转运车辆线路设计和运力规划模型。为提高模型求解效率,将模型拆解为开行路径优化和开行方案优化两个子问题,把第一个子问题转换为旅行商问题,将获得的备选线路路径作为第二个子问题的输入进行模型求解。依托成都市轨道交通网络和早高峰时段的客流数据,验证不同限流强度下所提模型的有效性,讨论了转运线路对停站点数量和停靠站点选取的偏好。结果表明,目标值表现良好的线路多为停站点为2~3个的路径,在停靠站点的选取上高度集中,对3~4个特定路径的偏好显著。随着限流强度的逐步加强,偏好于选择停站数量较少,走行距离较短的线路以达到快速转运的需求。在开行班次的选取上,整体上呈现线性增长趋势,但当限流强度大于0.8时,单一线路难以满足转运需求,不再保持线性增长趋势。

关键词:

"> 综合运输;客流转运;协同优化;地铁客流;客流控制;旅行商问题

Abstract:

To address the current gaps in managing the restricted passenger flow transfers in urban rail transit networks, this study investigates the planning of transfer vehicle routes and capacity allocation under specific flow control conditions. First, the utility and selection probability of passengers opting for transfer vehicles are analyzed and quantified across various route conditions. Then, a model for the design of transfer bus routes and capacity planning under flow control scenarios is proposed, aiming to minimize total expected travel time, minimize the operational costs of transfer vehicles, and maximize the alleviation of passenger congestion in the rail transit network. To enhance model-solving efficiency, the model is divided into two subproblems: route optimization and service optimization. The first subproblem is transformed into a traveling salesman problem, with the resulting alternative route paths serving as input for solving the second subproblem. Using passenger flow data from the Chengdu rail transit network during peak morning hours, the method is validated under varying flow control intensities. The study also explores preferences in transfer routes based on the number of stops and the selection of stop locations. Results indicate that the routes yielding optimal objective values generally consist of paths with two to three stops, showing high concentration in stop selection and a strong preference for three to four specific routes. As flow control intensity increases, there is a marked preference for routes with fewer stops and shorter travel distances to meet rapid transfer demands. In terms of service frequency, a linear growth trend is observed overall, however, when flow control intensity exceeds 0.8, a single route can no longer meet transfer demands, leading to a departure from the linear growth trend.

Key words: integrated transportation, passenger transit, collaborative optimization, metro passenger flow, passenger flow control, traveling salesman problem