考虑行程时间波动的电动公交可变行车计划

doi:10.16097/j.cnki.1009-6744.2023.01.017

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (1): 152-164.DOI: 10.16097/j.cnki.1009-6744.2023.01.017

考虑行程时间波动的电动公交可变行车计划

汪怡然¹，莫鹏里¹，别一鸣²，徐志红³，万剑⁴，刘志远^*1

1. 东南大学，交通学院，南京 211189；2. 吉林大学，交通学院，长春 130022；3. 悉地(苏州)勘察设计顾问有限公司，江苏苏州 215000；4. 华设设计集团股份有限公司，智能交通技术和设备交通运输行业研发中心，南京 210014

收稿日期:2022-09-07 修回日期:2022-11-11 接受日期:2022-11-22 出版日期:2023-02-25 发布日期:2023-02-16
作者简介:汪怡然(1997- )，女，安徽马鞍山人，博士生。
基金资助:
国家优秀青年科学基金(71922007)

Optimization of Variable Electric Bus Schedule Considering Volatility in Trip Travel Time

WANG Yi-ran¹, MO Peng-li¹, BIE Yi-ming², XU Zhi-hong³, WAN Jian⁴, LIU Zhi-yuan^*1

1. School of Transportation, Southeast University, Nanjing 211189, China; 2. School of Transportation, Jilin University, Changchun 130022, China; 3. CCDI (Suzhou) Exploration & Design Consultant Co. Ltd., Suzhou 215000, Jiangsu, China; 4. Research and Development Center on ITS Technology and Equipment, China Design Group Co. Ltd., Nanjing 210014, China

Received:2022-09-07 Revised:2022-11-11 Accepted:2022-11-22 Online:2023-02-25 Published:2023-02-16
Supported by:
Distinguished Young Scholar Project (71922007)

摘要/Abstract

摘要： 为解决因运行时间不确定性导致的公交到发时间不准点问题，本文基于公交线路双方向发车趟次和运营时间的不对称特征，提出一种可变行车计划优化问题。以最小化车辆使用数和乘客等待时间为目标，考虑车次链的行程接续和电动公交车辆电量等约束，构建公交时刻表和车辆排班一体化优化模型。根据可变行车计划优化问题特性设计改进的粒子群算法(Modified Particle Swarm Optimization for Timetabling and Scheduling, MPSO-TS)进行求解，定制粒子编码和子代更新方式。采用“基于优势车次链”的子代更新机制，以“车次链”为纽带最大程度地保留父代被继承信息中时刻表与车辆调度方案之间的关联性。使用连云港市某公交线路验证模型和算法，案例结果表明：可变行车计划能够有效保证车辆到发准点性，通过更紧密的排班计划将使用车数由35辆减少至31辆，车辆使用效率提升了28.1%；所提出的MPSO-TS算法求解效率较高，具有较好的稳定性，可有效避免计算结果陷入“局部最优”。

关键词: 交通工程, 可变行车计划, 一体化优化, 时刻表制定, 车辆排班方案设计, 电动公交

Abstract: A variable bus schedule optimization model based on asymmetric characteristics in two directions, including the number of frequencies and operating time, was proposed to cope with the inaccurate timetable caused by random fluctuations in trip travel time. The model combined bus timetabling and vehicle scheduling under the constraints of trip connectivity and battery state of charge to minimize the number of vehicles and passengers' waiting time. A modified particle swarm optimization algorithm, called modified particle swarm optimization for timetabling and scheduling (MPSO-TS), was tailored to tackle the integrated optimization problem of bus timetabling and vehicle scheduling. Besides, a customized particle encoding and offspring update method was provided. The offspring update method was built on the "dominant vehicle chain", wherein the "vehicle chain" can help to inherit the relevance between the timetable and vehicle scheduling from the parent generation. A bus line in Lianyungang, China, was taken to verify the proposed model and algorithm. The results show that the proposed method can ensure the punctuality of timetable. Moreover, the proposed method generates a tighter vehicle schedule and reduces the number of vehicles used from 35 to 31. The vehicles' utilization is effectively increased by 28.1%. The proposed MPSO-TS has a high level of efficiency and stability, as well as a powerful capacity to avoid from being trapped in the local optimum.

Key words: traffic engineering, variable bus schedules, integrated optimization, timetabling, vehicle scheduling, electric bus

中图分类号:

U491.1

汪怡然, 莫鹏里, 别一鸣, 徐志红, 万剑, 刘志远. 考虑行程时间波动的电动公交可变行车计划[J]. 交通运输系统工程与信息, 2023, 23(1): 152-164.

WANG Yi-ran, MO Peng-li, BIE Yi-ming, XU Zhi-hong, WAN Jian, LIU Zhi-yuan. Optimization of Variable Electric Bus Schedule Considering Volatility in Trip Travel Time[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(1): 152-164.

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参考文献

[1] SHANG H Y, HUANG H J, WU W X. Bus timetabling considering passenger satisfaction: An empirical study in Beijing[J]. Computers and Industrial Engineering, 2019, 135: 1155-1166.

[2] 马晓磊, 沈宣良, 张钊, 等. 基于拉格朗日松弛算法的自动驾驶公交调度优化研究[J]. 中国公路学报, 2019, 32(12): 10-24. [MA X L, SHEN X L, ZHANG Z, et al. Optimization of autonomous bus scheduling based on lagrangian relaxation[J]. China Journal of Highway and Transport, 2019, 32(12): 10-24.]

[3] ZHANG W Y, XIA D Y, LIU T, et al. Optimization of single-line bus timetables considering time-dependent travel times: A case study of Beijing, China[J]. Computers and Industrial Engineering, 2021, 158: 107444.

[4] WANG Y, ZHANG D X, HU L, et al. A data-driven and optimal bus scheduling model with time-dependent traffic and demand[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(9): 2443-2452.

[5] GKIOTSALITIS K. Bus scheduling considering tripvarying travel times, vehicle availability and capacity[J]. IET Intelligent Transport Systems, 2020, 14(12): 1594- 1605

[6] BIE Y M, JI J H, WANG X Y, et al. Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption[J]. ComputerAided Civil and Infrastructure Engineering, 2021, 36 (12): 1530-1548.

[7] 刘昊翔, 吴啊峰, 龙建成, 等. 基于列生成启发式的单线电动公交车与司机整合调度优化[J]. 交通运输系统工程与信息, 2021, 21(4): 211-220. [LIU H X, WU A F, LONG J C, et al. Column generation-based heuristic approach for electric bus and driver scheduling on single bus lines[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 211-220.]

[8] TENG J, CHEN T, FAN W. Integrated approach to vehicle scheduling and bus timetabling for an electric bus line[J]. Journal of Transportation Engineering, Part A: Systems, 2020, 146(2): 04019073.

[9] VAN LIESHOUT R N. Integrated periodic timetabling and vehicle circulation scheduling[J]. Transportation Science, 2021, 55(3): 768-790.

[10] 程春阳. 公交电动车辆的智能排班方法研究[D]. 北京: 北京邮电大学, 2019. [CHENG C Y. The research on electric bus scheduling based on intelligent optimization algorithm[D]. Beijing: Beijing University of Posts and Telecommunications, 2019.]

[11] 张景, 沈吟东. 基于定位数据的公交时间站点自动选择方法[J]. 交通运输系统工程与信息, 2012, 12(6): 60- 65, 163. [ZHANG J, SHEN Y D. Automatic selection of time points based on AVL data[J]. Journal of Transportation Systems Engineering and Information Technology, 2012, 12(6): 60-65, 163.]

[12] CEDER A. Public transit planning and operation: Modeling, practice and behavior[M]. Boca Raton: CRC press, 2016.

[13] LI J Q. Transit bus scheduling with limited energy[J]. Transportation Science, 2014, 48(4): 521-539.

[14] 中华人民共和国交通运输部. 交通运输部关于印发《国家公交都市建设示范工程管理办法》的通知[EB/ OL]. (2022-4-11) [2022-7-27]. https://xxgk.mot.gov.cn/ 2020/ jigou/ ysfws/ 202204/ t20220411_3650428. html. [Ministry of Transport of the People's Republic of China. Circular of the ministry of transport on measures for the administration of the national program to improve public transport [EB/OL]. (2022-4-11) [2022-7-27]. https:// xxgk. mot. gov. cn/ 2020/ jigou/ ysfws/ 202204/ t20220411_3650428.html.]

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考虑行程时间波动的电动公交可变行车计划

Optimization of Variable Electric Bus Schedule Considering Volatility in Trip Travel Time

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