兼顾效率与公平的城市轨道交通客流控制优化

doi:10.16097/j.cnki.1009-6744.2024.06.009

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (6): 102-112.DOI: 10.16097/j.cnki.1009-6744.2024.06.009

兼顾效率与公平的城市轨道交通客流控制优化

梁金鹏^1a ，赵莲芳^1a ，李利鸣^1b ，郑建风^*1a ，宋达宽²

1. 大连海事大学，a.交通运输工程学院，b.航运经济与管理学院，辽宁大连116026； 2. 大连公共交通建设投资集团有限公司，辽宁大连116011

收稿日期:2024-07-06 修回日期:2024-09-12 接受日期:2024-09-23 出版日期:2024-12-25 发布日期:2024-12-18
作者简介:梁金鹏(1989- )，男，山东烟台人，副教授。
基金资助:
国家自然科学基金(72101042, 72371046)。

Urban Rail Transit Passenger Flow Control Considering Efficiency and Fairness

LIANG Jinpeng^1a,ZHAO Lianfang^1a,LI Liming^1b,ZHENG Jianfeng^*1a,SONG Dakuan²

1a. College of Transportation Engineering, 1b. School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, Liaoning, China; 2. Dalian Public Transport Construction Investment Group Co Ltd, Dalian 116011, Liaoning, China

Received:2024-07-06 Revised:2024-09-12 Accepted:2024-09-23 Online:2024-12-25 Published:2024-12-18
Supported by:
NationalNaturalScienceFoundation of China (72101042, 72371046)。

摘要/Abstract

摘要： 高峰时段客流拥挤是大城市轨道交通面临的关键挑战，其不仅增加站内客流踩踏事故风险，还导致上下游车站的乘客等待时间存在显著差异。针对客流需求的随机性和动态性特点，本文构建一个旨在提高出行效率并改善乘客出行公平性的多目标客流控制优化模型。该模型通过合理确定各站点乘客的上车比例，在满足可行性约束条件下，优化所有乘客平均等待时间(效率)和每个站点乘客平均等待时间(公平性)与理想值间的欧式距离。为求解该多目标随机优化模型，本文开发了在线优化算法，针对每种需求场景制定客流控制决策。基于北京地铁5号线客流数据的数值实验结果表明，与先到先服务的基准策略相比，该策略能显著提升运营效率并改善公平性。此外，该算法能得到与Gurobi直接求解相近的结果，同时，将计算时间降低了76.3%。本文为解决高峰时段轨道交通客流拥挤问题提供了有效的策略和方法论参考。

关键词: 城市交通, 客流控制, 多目标优化, 客流拥挤, 在线优化算法

Abstract: Passenger overcrowding during peak hours is a critical challenge in urban rail transit of large cities. It not only increases the risk of passenger stampede accidents within stations but also leads to significant differences in waiting times between upstream and downstream stations. Considering the stochastic and dynamic nature of passenger demand, this paper develops a multi-objective passenger flow control optimization model that aims to enhance travel efficiency and improve passenger travel fairness. The model can determine reasonable boarding ratio of passengers at each station, and optimize the average waiting time of all passengers (efficiency) and the Euclidean distance between the average waiting time of passengers at each station (fairness) and the ideal value under the feasibility constraints. To solve this multi-objective stochastic optimization model, an online optimization algorithm is developed to make passenger flow control decisions for each demand scenario. Numerical experiments based on passenger flow data from Beijing Metro Line 5 show that, compared to the benchmark first-come-first-served policy, the proposed method can significantly improve operational efficiency and fairness. Moreover, the algorithm achieves results close to those obtained by direct solving with Gurobi while reducing the computation time by 76.3%. This paper provides an effective strategy and methodological reference for addressing the problem of passenger overcrowding in urban rail transit during peak hours.

Key words: urban traffic, passenger flow control, multi-objective optimization, passenger congestion, online algorithm

中图分类号:

U293.5

梁金鹏, 赵莲芳, 李利鸣, 郑建风, 宋达宽. 兼顾效率与公平的城市轨道交通客流控制优化[J]. 交通运输系统工程与信息, 2024, 24(6): 102-112.

LIANG Jinpeng, ZHAO Lianfang, LI Liming, ZHENG Jianfeng, SONG Dakuan. Urban Rail Transit Passenger Flow Control Considering Efficiency and Fairness[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(6): 102-112.

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http://www.tseit.org.cn/CN/Y2024/V24/I6/102

参考文献

[1]鲁工圆,马驷,王坤,等.城市轨道交通线路客流控制整数规划模型[J]. 西南交通大学学报, 2017, 52(2): 319-325. [LU G Y, MA S, WANG K, et al. Integer programming model of passenger flow assignment for congested urban rail lines[J]. Journal of Southwest Jiaotong University, 2017, 52(2): 319-325.]

[2]SHI J G, YANG L X, YANG J, et al. Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach[J]. Transportation Research Part B: Methodological, 2018, 110: 26-59.

[3] XU X Y, LI H Y, LIU J, et al. Passenger flow control with multi-station coordination in subway networks: Algorithm development and real-world case study[J]. Transportmetrica B: Transport Dynamics, 2019, 7(1): 446-472.

[4]赵鹏,姚向明,禹丹丹.高峰时段城市轨道交通线路客流协调控制[J]. 同济大学学报(自然科学版),2014,42 (9): 1340-1346, 1443. [ZHAO P, YAO X M, YU D D. Cooperative passenger inflow control of urban mass transit in peak hours[J]. Journal of Tongji University (Natural Science), 2014, 42(9): 1340-1346, 1443.]

[5]姚向明,赵鹏,乔珂,等.城市轨道交通网络客流协同控制模型[J]. 中南大学学报(自然科学版),2015,46(1): 342-350. [YAO X M, ZHAO P, QIAO K, et al. Modeling on coordinated passenger inflow control for urban rail transit network[J]. Journal of Central South University (Science and Technology), 2015, 46(1): 342 350.]

[6]李登辉,彭其渊,鲁工圆,等.城市轨道交通高峰线路客流协同控制方法[J]. 交通运输系统工程与信息, 2019, 19(6): 141-147. [LI D H, PENG Q Y, LU G Y, et al. Control method for passenger inflow control with coordination on urban rail transit line in peak hours[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(6): 141-147.]

[7] MENG F T, YANG L X, SHI J G, et al. Collaborative passenger flow control for oversaturated metro lines: A stochastic optimization method[J]. Transportmetrica A: Transport Science, 2022, 18(3): 619-658.

[8]LU Y H, YANG L X, YANG H, et al. Robust collaborative passenger flow control on a congested metro line: A joint optimization with train timetabling[J]. Transportation Research Part B: Methodological, 2023, 168: 27-55.

[9] HU Y T, LI S K, WANG Y H, et al. Robust metro train scheduling integrated with skip-stop pattern and passenger flow control strategy under uncertain passenger demands[J]. Computers and Operations Research, 2023, 151: 106116.

[10] 贾斌, 朱凌, 李树凯,等.城市轨道交通小交路计划与客流控制协同优化策略[J].交通运输系统工程与信息, 2022, 22(1): 124-132. [JIA B, ZHU L, LI S K, et al. Collaborative optimization strategy of short-turning plan and passenger flow control in urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 124-132.]

[11] LIANG J P, ZANG G Z, LIU H T, et al. Reducing passenger waiting time in oversaturated metro lines with passenger flow control policy[J]. Omega, 2023, 117: 102845.

[12] 蒋琦玮,苏建凯,陈维亚.考虑跨站停车的地铁客流协同控制模型[J]. 铁道科学与工程学报,2021, 18(11): 2857-2864. [JIANG Q W, SU J K, CHEN W Y. Collaborative control model of metro passenger flow considering skip-stop strategy[J]. Journal of Railway Science and Engineering, 2021, 18(11): 2857-2864.]

[13] 陈维亚, 章雍,陈鑫,等.城市轨道交通大小交路开行方案与多站联合限流协同优化研究[J].交通运输系统工程与信息, 2019, 19(5): 177-184. [CHEN W Y, ZHANG Y, CHEN X, et al. Collaborative full-length and short-turning plan and joint multi-station control of passenger flow in urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(5): 177-184.]

[14] SUN L J, JIN J G, LEE D, et al. Demand-driven timetable design for metro services[J]. Transportation Research Part C: Emerging Technologies, 2014, 46: 284 299.

[15] LIANG J P, LYU G D, TEO C P, et al. Online passenger flow control in metro lines[J]. Operations Research, 2023, 71(2), 768-775.

兼顾效率与公平的城市轨道交通客流控制优化

Urban Rail Transit Passenger Flow Control Considering Efficiency and Fairness

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