考虑空间需求不均的模块化公交线路运行方案优化研究

doi:10.16097/j.cnki.1009-6744.2024.04.016

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (4): 166-175.DOI: 10.16097/j.cnki.1009-6744.2024.04.016

考虑空间需求不均的模块化公交线路运行方案优化研究

易洪波^1a,2，刘昱岗^*1a,1b,1c，王童语^1a

1. 西南交通大学，a.交通运输与物流学院，b.综合交通运输智能化国家地方联合工程实验室，c.综合交通大数据应用技术国家工程实验室，成都611756；2.纽约大学阿布扎比分校，工程系，阿布扎比129188，阿拉伯联合酋长国

收稿日期:2024-04-26 修回日期:2024-05-15 接受日期:2024-05-20 出版日期:2024-08-25 发布日期:2024-08-22
作者简介:易洪波(1995- )，男，湖南张家界人，博士生。
基金资助:
国家自然科学基金 (51774241)；国家留学基金管理委员会奖学金 (202307000073)。

Optimizing Modular Bus Route Operation Considering Spatially Uneven Demand

YI Hongbo,LIU Yugang,WANG Tongyu

1a. School of Transportation and Logistics, 1b. National United Engineering Laboratory of Integrated and Intelligent Transportation, 1c. National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 611756, China; 2. Division of Engineering, New York University Abu Dhabi, Saadiyat Marina District PO Box 129188,Abu Dhabi UnitedArab Emirates

Received:2024-04-26 Revised:2024-05-15 Accepted:2024-05-20 Online:2024-08-25 Published:2024-08-22
Supported by:
NationalNaturalScienceFoundation of China (51774241)； China Scholarship Council (CSC) Scholarships (202307000073)。

摘要/Abstract

摘要： 传统固定容量公交车辆难以应对公交线路上空间分布不均的需求。为解决这一问题，引入模块化公交车辆，通过编组与解编的方式实现车队在运行中的容量动态变化，以更贴合需求在空间上的变化。基于运行时空图重构的方法，建立描述模块化公交线路运行方案的优化模型，所构建模型为混合整数非线性规划(MixedInteger-Nonlinear Program, MINLP)模型，模型决策变量包括车队的运行方案以及模块化公交单元的运行方案。为方便求解，采用时间离散化手段，通过一系列方法将所构建的MINLP模型转化为易于求解的混合整数线性规划(MixedInteger-Linear Program, MILP)模型，并基于成都市真实公交线路与乘客需求数据进行案例分析。实验结果表明，与传统容量固定式公交相比，模块化公交的应用能够使乘客成本降低11.44%，运营成本降低31.35%，综合降低20.32%的系统总成本。敏感性分析实验结果分析了系统供给与需求变化对系统成本产生的影响。

关键词: 城市交通, 运行方案优化, 混合整数非线性优化模型, 模块化公交, 时间离散化, Gurobi

Abstract: Traditional fixed-capacity buses struggle to meet the varying demand distribution on bus routes. To tackle this challenge, modular buses are introduced, allowing for dynamic adjustments in platoon capacity through joining and detaching, thus better accommodating spatial demand variations. An optimization model is developed to describe the operational scheme of modular bus routes, based on the reconstruction of spatiotemporal graphs. The formulated model, a Mixed Integer-Nonlinear Program (MINLP) model, includes decision variables such as platoon schemes and modular bus unit schemes. To facilitate the model solution, time discretization is applied, which transforms the MINLP model into a Mixed Integer-Linear Program (MILP). A case study is performed using real bus routes and passenger demand data from Chengdu, China. Experimental results demonstrate that the use of modular buses reduces passenger costs by 11.44% and operating costs by 31.35% compared to traditional fixed-capacity buses, resulting in an overall decrease of 20.32% in total system costs. Sensitivity analysis experiments examine the effect of system supply and demand changes on system costs.

Key words: urban traffic, route optimization, mixed integer-nonlinear program(MINLP), modular bus, time discretization, Gurobi

中图分类号:

U121

易洪波, 刘昱岗, 王童语. 考虑空间需求不均的模块化公交线路运行方案优化研究[J]. 交通运输系统工程与信息, 2024, 24(4): 166-175.

YI Hongbo, LIU Yugang, WANG Tongyu. Optimizing Modular Bus Route Operation Considering Spatially Uneven Demand[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(4): 166-175.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2024.04.016

http://www.tseit.org.cn/CN/Y2024/V24/I4/166

参考文献

[1] 任婧璇,常孝亭,巫威眺,等.考虑候选站点和全服务过程的需求响应接驳公交调度[J].交通运输系统工程与信息,2023, 23(5): 202-214. [REN J X, CHANG X T, WU W T, et al. Demand responsive feeder transit scheduling considering candidate stops and full-service process[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 202-214.]

[2]李光春,聂磊.基于改进自适应大邻域算法的公交线网规划方法[J]. 交通运输系统工程与信息,2023,23 (5): 96-103. [LI G C, NIE L. Bus network planning method based on improved adaptive large neighborhood search algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 96-103.]

[3]TIAN Q, HUI Y, WANG D Z W. Joint scheduling and formation design for modular-vehicle transit service with time-dependent demand[J]. Transportation Research Part C: Emerging Technologies, 2023, 147(1): 103986.

[4]PEI M, LIN P, DU J, et al. Vehicle dispatching in modular transit networks: A mixed integer nonlinear programming model[J]. Transportation Research Part E: Logistics and Transportation Review, 2021, 147: 102240.

[5]DAKIC I, YANG K, MENENDEZ M, et al. On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram[J]. Transportation Research Part B: Methodological, 2021, 148: 38-59.

[6]HANNOUN G J, MENENDEZ M. Modular vehicle technology for emergency medical services[J]. Transportation Research Part C: Emerging Technologies, 2022, 140: 103694.

[7] KHAN Z S, HE W, MENENDEZ M. Application of modular vehicle technology to mitigate bus bunching[J]. Transportation Research Part C: Emerging Technologies, 2023, 146(1): 103953.

[8] CHEN Z, LI X, QU X. A continuous model for designing corridor systems with modular autonomous vehicles enabling station-wise docking[J]. Transportation Science, 2022, 56(1): 1-30.

[9] SHI X, LI X. Operations design of modular vehicles on an oversaturated corridor with first-in, first-out passenger queueing[J]. Transportation Science, 2021, 55(5): 1187 1205.

[10] DAI Z, LIU X C, CHEN X, et al. Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: A dynamic programming approach[J]. Transportation Research Part C: Emerging Technologies, 2020, 114: 598-619.

[11] TIAN Q, LIN Y H, WANG D Z W, et al. Planning for modular-vehicle transit service system: Model formulation and solution methods[J]. Transportation Research Part C: Emerging Technologies, 2022, 138(1): 103627.

[12] 范文博,陈香,刘涛.模块化自动驾驶穿梭公交服务频率优化及时刻表设计[J].交通运输工程与信息学报, 2023, 21(2): 160-176. [FAN W B, CHEN X, LIU T. Modular autonomous shuttle transit service: Frequency setting and timetabling[J]. Journal of Transportation Engineering and Information, 2023, 21(2): 160-176.]

[13] YI H, LIU Y, MENENDEZ M, et al. Charging scheduling and route planning for modular bus systems considering non-linear charging profile[J/OL], SSRN, (2024-04-05) [2024-04-26]. http://dx.doi.org/10.2139/ssrn.4785233.

[1]	刘涛, 郭家新, 韩莹, 唐春艳. 氢燃料电池公交研究文献综述及展望[J]. 交通运输系统工程与信息, 2024, 24(5): 1-13.
[2]	张兰怡, 徐艺诺, 王硕, 谢郑一, 翁大维, 王振昊, 胡喜生, 郑娉婷. 碳达峰背景下沿海城市群道路交通节能减排潜力[J]. 交通运输系统工程与信息, 2024, 24(5): 45-55.
[3]	张雅丽, 付锐, 魏文辉, 袁伟, 郭应时. 考虑速度模式的纯电动公交进出站生态驾驶策略[J]. 交通运输系统工程与信息, 2024, 24(5): 103-115.
[4]	茧敏, 陈绍宽, 王卓, 李昊. 城市轨道交通网络跨线列车开行方案优化模型研究[J]. 交通运输系统工程与信息, 2024, 24(5): 116-127.
[5]	孙元广, 邓澄远, 彭磊, 陈虹兵, 李纵然, 柏赟. 潮汐客流需求驱动的地铁列车不成对运行图节能优化方法[J]. 交通运输系统工程与信息, 2024, 24(5): 128-139.
[6]	岳昊, 董显龙, 王力, 曲秋莳, 张旭. 模块化公交系统车辆单元动态编组方案优化[J]. 交通运输系统工程与信息, 2024, 24(5): 160-172.
[7]	户佐安, 曾添, 杜俊, 魏易东, 王士博, 马毅. 双足运动微观视角下单列行人流建模与仿真研究[J]. 交通运输系统工程与信息, 2024, 24(5): 185-196.
[8]	金溪, 穆延. 暴雨内涝下城市路网抗涝韧性评估[J]. 交通运输系统工程与信息, 2024, 24(5): 226-236.
[9]	陈坚, 陈嘉果, 陈琦, 刘柯良, 代雪杨. 山地城市道路交通碳排放影响因素非线性关系模型[J]. 交通运输系统工程与信息, 2024, 24(5): 237-245.
[10]	牛振宁, 安琨, 马万经. 车网互动场景下电动网约车运营与充放电动态调度策略[J]. 交通运输系统工程与信息, 2024, 24(4): 50-59.
[11]	邓明君, 李书行, 李响, 张兵, 薛运强. 基于主线密度预测的快速路入口匝道控制方法[J]. 交通运输系统工程与信息, 2024, 24(4): 94-104.
[12]	李铁柱, 谢炳言, 刘天昊, 陈海波, 王召. 基于规则的信号交叉口纯电动公交节能驾驶策略[J]. 交通运输系统工程与信息, 2024, 24(4): 139-150.
[13]	姚恩建, 王鑫, 刘莎莎, 杨扬, 李成. 考虑机会充电与行程时间可靠性的区域多车型电动公交调度优化[J]. 交通运输系统工程与信息, 2024, 24(4): 151-165.
[14]	熊杰, 梁晶晶, 李向楠, 窦雪萍, 李同飞. 考虑分时电价和多车型的电动公交行车计划优化[J]. 交通运输系统工程与信息, 2024, 24(4): 188-199.
[15]	李洪运, 江志彬, 谷金晶, 刘伟, 王炳勋. 轨道交通远郊区段计划性停运对常乘客的转移影响[J]. 交通运输系统工程与信息, 2024, 24(4): 212-222.

考虑空间需求不均的模块化公交线路运行方案优化研究

Optimizing Modular Bus Route Operation Considering Spatially Uneven Demand

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics