城市轨道交通分时定价策略的公益性水平评价

doi:10.16097/j.cnki.1009-6744.2025.05.022

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (5): 248-260.DOI: 10.16097/j.cnki.1009-6744.2025.05.022

城市轨道交通分时定价策略的公益性水平评价

孟冉¹，杨洋^*2，宋子龙³

1. 河北经贸大学，管理科学与信息工程学院，石家庄050000；2.北京交通大学，交通运输学院，北京100044；3. 香港理工大学，香港999077

收稿日期:2025-04-15 修回日期:2025-09-09 接受日期:2025-09-10 出版日期:2025-10-25 发布日期:2025-10-25
作者简介:孟冉(1990—)，女，河北邢台人，讲师，博士。
基金资助:
河北省高等学校科学研究项目(BJ2025190)；国家自然科学基金(52572336)。

Evaluating Public Welfare Level of Time-sharing Pricing Strategy for Urban Rail Transit

MENG Ran¹,YANG Yang^*2, SONG Zilong³

1. School of Management Science and Information Engineering, Hebei University of Economics and Business, Shijiazhuang 050000, China; 2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 3. The Hong Kong Polytechnic University, Hong Kong 999077, China

Received:2025-04-15 Revised:2025-09-09 Accepted:2025-09-10 Online:2025-10-25 Published:2025-10-25
Supported by:
Science Research Project of Hebei Education Department (BJ2025190)；National Natural Science Foundation of China (52572336)。

摘要/Abstract

摘要： 为研究城市轨道交通分时定价的票价方案和公益性水平评价问题，本文从公益性角度出发，考虑票价和客流量的相互作用关系，以各时段的票价率为决策变量，基于交通方式影响因素和乘客出行选择行为，构建以系统乘客总出行时间最小为目标的双层规划模型；设计基于嵌套Method of Successive Averages的混合多种群遗传算法的求解方法；采用实际数据标定模型中关键参数，分析比较不同分时定价方案的票价率和公益性水平，提出基于公益性的分时定价方案。研究结果表明：在分时定价策略的效果中，能较明显地提升系统城市轨道交通公益性水平的方案为差别定价(高峰和非高峰票价下限和上限相同)和仅非高峰期降价策略，其中，前者的非高峰期和高峰期票价分别为0.1元·人^-1·km^-1和0.2元·人^-1·km^-1，相对于原票价方案使总广义费用和总出行时间分别降低12.75%和8.23%；较明显地降低公益性水平的方案为仅高峰期升价策略。

关键词: 城市交通, 差别定价, 双层规划模型, 城市轨道交通, 公益性, 客运结构

Abstract: This paper investigates the urban rail transit fare scheme and public welfare level of the time-sharing pricing strategy. Considering the interaction between urban rail transit fare and passenger flow, the study defines the fare rate of each time period as the decision variable and develops a two-level programming model with the goal of minimizing passengers total travel time of based on transportation mode and passenger travel choice behavior. A solution algorithm is designed based on a hybrid multi-population genetic algorithm with nested Method of Successive Averages. The field data was used to calibrate the key parameters in the model and analyze the fare rates and public welfare levels of different time-sharing pricing schemes. A time-sharing pricing scheme is then proposed based on public welfare. The results show that the schemes that can significantly improve the public welfare level of urban rail transit system include differential pricing (the lower and upper limits of peak and off-peak fares are the same) and price reduction strategy during the off-peak period. The off-peak and peak fares for the former are 0.1 and 0.2 yuan person^-1⋅km^-1, which reduces the total generalized cost and total travel time by 12.75% and 8.23% respectively compared with the traditional fare scheme. The scheme that significantly reduces the public welfare level is the strategy that increases price during peak hours.

Key words: urban traffic, differential pricing, two-level programming model, urban rail transit, public welfare, passenger transport structure

中图分类号:

U121

孟冉, 杨洋, 宋子龙. 城市轨道交通分时定价策略的公益性水平评价[J]. 交通运输系统工程与信息, 2025, 25(5): 248-260.

MENG Ran, YANG Yang, SONG Zilong. Evaluating Public Welfare Level of Time-sharing Pricing Strategy for Urban Rail Transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(5): 248-260.

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参考文献

[1] 毛保华,张政,陈志杰,等. 城市轨道交通网络化运营组织技术研究评述[J]. 交通运输系统工程与信息, 2017, 17(6): 155-163. [MAO B H, ZHANG Z, CHEN Z J, et al. A review on operational technologies of urban rail transit networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6): 155-163.]

[2] 彭恺,李夏苗.我国城市轨道交通网络运营盈利能力的实证分析[J]. 交通运输系统工程与信息, 2022, 22(6): 68-73, 104. [PENG K, LI X M. Empirical analysis on operational profitability of urban rail network in China [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 68-73, 104.]

[3] LIU Y, CHARLES P. Australasian transport research forum 2013 proceedings, queensland university of technology, 2013(C). Perth: The Planning and Transport Research Centre (PATREC), 2013.

[4] BERTOLETTI P. A note on ramsey pricing and the structure of preferences[J]. Journal of Mathematical Economics, 2018, 76: 45-51.

[5] WANG Q, ZHAO W J, MA S F, et al. Effects of a price incentive policy on urban rail transit passengers: A case study in Nanjing, China[J].Transportation Research, Part A: Policy and Practice, 2023, 178: 103879.

[6] ZHOU F Q, LI C F, HUANG Z Y, et al. Fare incentive strategies for managing peak-hour congestion in urban rail transit networks[J]. Transportation A: Transport Science, 2020(3): 1-37.

[7] HUAN N, HESS S, YAO E J, et al. Time-dependent pricing strategies for metro lines considering peak avoidance behaviour of commuters[J]. Transportmetrica A: Transport Science, 2022, 18(3): 1420-1444.

[8] YAO X M, CHEN L S, ZHAO P, et al. Exploring travelers' responses to a prepeak discount fare policy and optimizing the pricing strategy to ease peak congestion: The case of Beijing subway[J]. Transportation Research Part A: Policy and Practice, 2025, 191: 104335.

[9] TANG Y L, JIANG Y, YANG H, et al. Modeling and optimizing a fare incentive strategy to manage queuing and crowding in mass transit systems[J]. Transportation Research Part B: Methodological, 2020, 138: 247-267.

[10] 林晓言, 罗燊.轨道交通公益性与经营性平衡新模式[M]. 北京: 社会科学文献出版社, 2018. [LIN X Y, LUO S. New balance mode of public welfare and business for rail transit[M]. Beijing: Social Science Academic Press, 2018.]

[11] GUZMAN L A, OCHOA J L, CARDONA S G, et al. Pro-poor transport subsidies: More user welfare and faster travel[J]. Transportation Research Part A: Policy and Practice, 2025, 195: 104454.

[12] 刘美银, 王建伟.考虑城市客运结构优化的城市轨道交通定价方法研究[J]. 交通运输系统工程与信息, 2017, 17(3): 53–59. [LIU M Y, WANG J W. Pricing method of urban rail transit considering the optimization of passenger transport structure[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(3): 53–59.]

[13] 朱宇婷. 考虑乘客出行效率的城市轨道交通列车行方案优化研究[D]. 北京: 北京交通大学, 2016. [ZHU Y T. An optimization research for train plan of urban rail transit with the consideration of passengers’ travel efficiency[D]. Beijing: Beijing Jiaotong University, 2016.]

[14] FISK C. Some developments in equilibrium traffic assignment[J]. Transportation Research Part B: Methodological, 1980, 14(3): 243–255.

[15] 陈坚, 杨飞,晏启鹏.多方式复合城市交通网络弹性需求随机用户平衡分配模型[J]. 计算机应用研究, 2012, 29(10): 3693–3696. [CHEN J, YANG F, YAN Q P. Stochastic user equilibrium assignment model of multimodal composite urban transportation network with elastic demand[J]. Application Research of Computers, 2012, 29(10): 3693–3696.]

[16] 北京交通发展研究院. 2021北京市交通发展年度报告 [R]. 北京: 北京交通发展研究院, 2021. [Beijing Transportation development research institute. 2021 Beijing transportation development annual report[R]. Beijing: Beijing Transportation Development Research Institute, 2021.]

[17] YAO J, SHI F, ZHOU Z, et al. Combinatorial optimization of exclusive bus lanes and bus frequencies in multi-modal transportation network[J]. Journal of Transportation Engineering, 2012, 138(12): 1422–1429.

[18] 中国城市轨道交通协会. 城市轨道交通2021年度统计和分析报告[R]. 北京: 中国城市轨道交通协会, 2022. [China Urban Rail Transit Association. Urban rail transit 2021 annual statistics and analysis report[R]. Beijing: China Urban Rail Transit Association, 2022.]

[19] 住房和城乡建设部城市交通基础设施监测与治理实验室. 2022年度中国主要城市通勤监测报告[R]. 北京: 中国城市规划设计研究院, 2022. [Urban Transportation Infrastructure Monitoring and Governance Laboratory of the Ministry of Housing and Urban-Rural Development. 2022 China’s major cities commute monitoring report[R]. Beijing: China Academy of Urban Planning and Design, 2022.]

[20] 王敏. 城市轨道交通线路服务水平评估与改善方法研究[D]. 北京: 北京交通大学, 2022. [WANG M. Evaluation with improvement of level of service for urban rail transit lines[D]. Beijing: Beijing Jiaotong University, 2022.]

[21] 邹庆茹, 姚向明, 赵鹏. 城市轨道交通峰前折扣定价方案编制模型[J]. 交通运输系统工程与信息, 2020, 20 (2): 13–19. [ZOU Q R, YAO X M, ZHAO P. Pre-peak discount pricing scheme compilation model for urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 13–19.]

城市轨道交通分时定价策略的公益性水平评价

Evaluating Public Welfare Level of Time-sharing Pricing Strategy for Urban Rail Transit

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