Dynamic game and carbon emission effects between urban ride-sourcing and cruise taxis

doi:10.3785/j.issn.1008-973X.2025.07.005

Journal of ZheJiang University (Engineering Science)

2025, Vol. 59

Issue (7): 1373-1384 DOI: 10.3785/j.issn.1008-973X.2025.07.005

Dynamic game and carbon emission effects between urban ride-sourcing and cruise taxis

Jinchi JIAO1(

),Jian SUN2,*(

),Xunyou NI3

1. School of Transportation Engineering, Chang’an University, Xi’an 710064, China
2. School of Future Transportation, Chang’an University, Xi’an 710064, China
3. School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China

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Abstract

To study the dynamic competitive relationship between ride-sourcing and cruise taxis in urban environments and their impact on traffic carbon emissions, the Herfindahl-Hirschman index (HHI) was introduced to quantify the competitiveness of urban taxis. A four-player game model encompassing the government and enterprises was constructed. Considering two distinct decision-making sequences, 16 potential game scenarios were proposed. Equilibrium points were computed using the Stackelberg model, leading to the identification of 8 stable game scenarios. Based on the game outcomes, carbon emissions were calculated by integrating the COPERT model and a modified Michaelis-Menten (T-M-M) equation. Taking Xi’an as a case study, relationships between vehicle numbers (including both ride-sourcing vehicles and cruise taxis) and vehicle kilometers traveled, as well as between vehicle fleet size and carbon emissions, were established. The theoretical optimal carbon emissions under the proposed game scenarios were calculated. Results show that maintaining an optimal ratio of ride-sourcing vehicles and cruise taxis within the range of 29∶35 to 1∶1 in Xi’an can effectively balance market stability and low-carbon objectives. The government can implement traffic restriction policies (e.g., driving bans based on license plates) to maintain a slightly larger fleet of cruise taxis relative to ride-sourcing vehicles, alongside introducing incentive policies to accelerate the electrification of the cruise taxi fleet.

Key words： urban transportation shared mobility taxis competition game theory carbon emissions

Received: 19 May 2024 Published: 25 July 2025

CLC:

U 491.1+2

Fund: 国家自然科学基金资助项目（52172319，71971138，72161012）.

Corresponding Authors: Jian SUN E-mail: 2022234048@chd.edu.cn;jiansun@chd.edu.cn

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Cite this article:

Jinchi JIAO,Jian SUN,Xunyou NI. Dynamic game and carbon emission effects between urban ride-sourcing and cruise taxis. Journal of ZheJiang University (Engineering Science), 2025, 59(7): 1373-1384.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2025.07.005 OR https://www.zjujournals.com/eng/Y2025/V59/I7/1373

城市网约车与巡游出租车动态博弈及碳排放效应研究

为了研究城市网约车和巡游出租车的动态竞争关系及其对交通碳排放的影响，引入赫芬达尔-赫希曼指数（HHI）度量城市出租车的竞争程度. 构建包括政府和企业在内的四方博弈模型，考虑2种决策顺序，提出16种博弈场景，运用斯坦克尔伯格模型计算均衡点，筛选得到8种稳定博弈情景. 基于博弈结果，将COPERT模型与改进的Michaelis-Menten（T-M-M）方程整合，计算碳排放量. 以西安市为例，构建车辆数量（含网约车和巡游出租车）与行驶里程，车辆保有量与碳排放间的关系，计算得出不同博弈策略下的理论最优碳排放量. 结果显示，西安市网约车与巡游出租车最优比例控制在29∶35到1∶1能够维持市场平衡和低碳环保. 政府可通过限行、限号政策使巡游出租车数量略多于网约车，出台鼓励政策推动巡游出租车电气化进程.

关键词： 城市交通, 共享出行, 出租汽车, 竞争, 博弈理论, 碳排放

Fig.1 Logical relationship of four-player game model

博弈场景	$ {P}_{\mathrm{R}} $	$ {P}_{\mathrm{T}} $
场景1. 严-监-合-合	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景2. 严-不-合-合	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景3. 宽-监-合-合	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{no} $
场景4. 宽-不-合-合	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景5. 严-监-合-违	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {F}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景6. 严-不-合-违	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {F}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景7. 宽-监-合-违	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ \dfrac{1}{2}F_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景8. 宽-不-合-违	$ {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景9. 严-监-违-合	$ {R}_{z} $+?$ {R}_{z} $?$ {F}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景10. 严-不-违-合	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {F}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景11. 宽-监-违-合	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $?$ \dfrac{1}{2}F_{z} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景12. 宽-不-违-合	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景13. 严-监-违-违	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {F}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {F}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景14. 严-不-违-违	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {F}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n}+\Delta {R}_{n} $?$ {F}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $
场景15. 宽-监-违-违	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $?$ \dfrac{1}{2}F_{z} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $?$ \dfrac{1}{2}F_{n} $
场景16. 宽-不-违-违	$ {R}_{z} $+$ \Delta {R}_{z} $?$ {C}_{\mathrm{z}\mathrm{o}} $	$ {R}_{n} $+$ \Delta {R}_{n} $?$ {C}_{\mathrm{n}\mathrm{o}} $

Tab.1 Net payoffs of ride-sourcing and cruise taxis under different game scenarios

Fig.2 Daily order volume of cruise taxis and ride-sourcing

Fig.3 Distribution of hourly order rate for cruise taxis and ride-sourcing

Fig.4 Grid division of main urban area in Xi’an

Tab.2 Herfindahl-Hirschman indexes statistics within main urban area of Xi’an (excerpt)

Tab.3 Regulations on degree of competition between ride-sourcing and cruise taxis

Fig.5 Distribution of competition degree between ride-sourcing and cruise taxis in main urban area of Xi’an

Tab.4 Parameters and assignments of game model

Tab.5 Nash equilibrium results of parameter assignment in different game scenarios (priority implementation strategy for ride-sourcing)

Tab.6 Nash equilibrium results of game scenarios

Tab.7 Removal notes for unstable game scenarios

Fig.6 Relationship between total carbon emissions and number of ride-sourcing vehicles

Fig.7 Comparison of total carbon emissions under particular cases

Fig.8 Variation of carbon emissions with ride-sourcing vehicles under particular cases

Fig.9 Impact of key model parameters on carbon emissions

Fig.10 Expectations and variances of key model parameters


[1]	张旭昆, 赵静互联网对市场的改善和扰乱: 基于市场失灵理论的视角[J]. 浙江大学学报: 人文社会科学版, 2019, 49 (2): 86- 99 ZHANG Xukun, ZHAO Jing Internet improvement and disruption to the market: from the perspective of market failure theory[J]. Journal of Zhejiang University: Humanities and Social Sciences, 2019, 49 (2): 86- 99

[2]	杨学成, 涂科出行共享中的用户价值共创机理: 基于优步的案例研究[J]. 管理世界, 2017, (8): 154- 169 YANG Xuecheng, TU Ke The co-creation mechanism of user value in travel sharing: a case study based on Uber[J]. Journal of Management World, 2017, (8): 154- 169 doi: 10.3969/j.issn.1002-5502.2017.08.013

[3]	易开刚, 张琦平台经济视域下的商家舞弊治理: 博弈模型与政策建议[J]. 浙江大学学报: 人文社会科学版, 2019, 49 (5): 127- 142 YI Kaigang, ZHANG Qi Analysis of sellers’ commercial fraud in platform economy based on evolutionary game theory[J]. Journal of Zhejiang University: Humanities and Social Sciences, 2019, 49 (5): 127- 142

[4]	孙启鹏, 王栋, 许晓晴, 等基于动态博弈的城市出租车投放量测算研究[J]. 交通运输系统工程与信息, 2019, 19 (5): 193- 197 SUN Qipeng, WANG Dong, XU Xiaoqing, et al Urban taxi quantity based on dynamic game theory[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19 (5): 193- 197

[5]	罗清和, 潘道远 “专车” 进入后的出租车市场规制策略研究[J]. 长安大学学报: 社会科学版, 2015, 17 (4): 34- 41 LUO Qinghe, PAN Daoyuan Research on the regulation strategy of the taxi market after the “special car” entering[J]. Journal of Chang’an University: Social Science Edition, 2015, 17 (4): 34- 41

[6]	VAN VUGT M, MEERTENS R M, VAN LANGE P A M Car versus public transportation? The role of social value orientations in a real-life social dilemma[J]. Journal of Applied Social Psychology, 1995, 25 (3): 258- 278 doi: 10.1111/j.1559-1816.1995.tb01594.x

[7]	PEDERSEN P A Moral hazard in traffic games[J]. Journal of Transport Economics and Policy, 2003, 37 (1): 47- 68

[8]	YANG H, ZHANG X, MENG Q Stackelberg games and multiple equilibrium behaviors on networks[J]. Transportation Research Part B: Methodological, 2007, 41 (8): 841- 861 doi: 10.1016/j.trb.2007.03.002

[9]	杨露萍, 钱大琳小汽车通勤向公共交通转移演化博弈分析[J]. 北京交通大学学报, 2014, 38 (2): 151- 156 YANG Luping, QIAN Dalin Evolutionary game analysis on modal shift of car commuters to public transport[J]. Journal of Beijing Jiaotong University, 2014, 38 (2): 151- 156 doi: 10.11860/j.issn.1673-0291.2014.04.27

[10]	SUN Q, HE Y, WANG Y, et al Evolutionary game between government and ride-hailing platform: evidence from China[J]. Discrete Dynamics in Nature and Society, 2019, 2019 (1): 9545102

[11]	杨浩雄, 魏彬网络约车与出租车的竞争博弈研究: 以平台补贴为背景[J]. 北京社会科学, 2016, (5): 68- 76 YANG Haoxiong, WEI Bin On the competition game between online tailored taxi and traditional taxi under platform’s subsidy policy[J]. Social Sciences of Beijing, 2016, (5): 68- 76

[12]	SUN S, WANG W Analysis on the market evolution of new energy vehicle based on population competition model[J]. Transportation Research Part D: Transport and Environment, 2018, 65: 36- 50 doi: 10.1016/j.trd.2018.08.005

[13]	蒋慧峰, 陈森发基于时不变综合系数的运输方式动力学模型[J]. 系统工程学报, 2010, 25 (1): 85- 90 JIANG Huifeng, CHEN Senfa Dynamic model of transportation modes based on time-invariant comprehensive coefficient[J]. Journal of Systems Engineering, 2010, 25 (1): 85- 90

[14]	SUN D J, JIAO J C, NI X Y, et al Modeling dynamic competition among urban taxis and the impact on carbon emissions[J]. Sustainable Cities and Society, 2025, 122: 106258 doi: 10.1016/j.scs.2025.106258

[15]	孙会君, 杨爽, 吕莹, 等数据驱动下共享出行资源配置的双层博弈问题研究[J]. 管理世界, 2023, 39 (4): 160- 175 SUN Huijun, YANG Shuang, LV Ying, et al Research on data-driven bi-level game problems in resource allocation of sharing mobility systems[J]. Journal of Management World, 2023, 39 (4): 160- 175

[16]	陈启香, 吕斌, 陈喜群, 等空间异质性建成环境对出租车与地铁竞合关系的影响[J]. 交通运输系统工程与信息, 2022, 22 (3): 25- 35 CHEN Qixiang, LV Bin, CHEN Xiqun, et al Impacts of built environment on competition and cooperation relationship between taxi and subway considering spatial heterogeneity[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22 (3): 25- 35

[17]	奉鸣, 信红喜, 骆冠良, 等未来我国出租车发展趋势及市场化改革研究[J]. 综合运输, 2023, 45 (4): 28- 32 FENG Ming, XIN Hongxi, LUO Guanliang, et al Development trend and market reform of China’s taxi in the future[J]. China Transportation Review, 2023, 45 (4): 28- 32

[18]	GRAHN R, HARPER C D, HENDRICKSON C, et al Socioeconomic and usage characteristics of transportation network company (TNC) riders[J]. Transportation, 2020, 47 (6): 3047- 3067 doi: 10.1007/s11116-019-09989-3

[19]	杨燕, 胥川出租车和网约车载客空间特征分析[J]. 交通运输工程与信息学报, 2020, 18 (1): 68- 76 YANG Yan, XU Chuan Analysis the spatial characteristic of taxi and ridesourcing service trips[J]. Journal of Transportation Engineering and Information, 2020, 18 (1): 68- 76 doi: 10.3969/j.issn.1672-4747.2020.01.009

[20]	韩印, 李媛媛, 李文翔, 等基于轨迹数据的网约车排放时空特征分析[J]. 交通运输系统工程与信息, 2022, 22 (1): 234- 242 HAN Yin, LI Yuanyuan, LI Wenxiang, et al Analyzing spatiotemporal characteristics of ridesourcing emissions based on trajectory data[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22 (1): 234- 242

[21]	ROBINSON R M, KHATTAK A Route change decision making by hurricane evacuees facing congestion[J]. Transportation Research Record, 2010, 2196 (1): 168- 175 doi: 10.3141/2196-18

[22]	HENRY E, FURNO A, EL FAOUZI N E Approach to quantify the impact of disruptions on traffic conditions using dynamic weighted resilience metrics of transport networks[J]. Transportation Research Record, 2021, 2675 (4): 61- 78 doi: 10.1177/0361198121998663

[23]	SHORSHANI F M, ANDRÉ M, BONHOMME C, et al Modelling chain for the effect of road traffic on air and water quality: techniques, current status and future prospects[J]. Environmental Modelling and Software, 2015, 64: 102- 123 doi: 10.1016/j.envsoft.2014.11.020

[24]	LI Y, ZHENG J, DONG S, et al Temporal variations of local traffic CO2 emissions and its relationship with CO2 flux in Beijing, China[J]. Transportation Research Part D: Transport and Environment, 2019, 67: 1- 15 doi: 10.1016/j.trd.2018.10.007

[25]	赵光辉, 李玲玲大数据时代新型交通服务商业模式的监管——以网约车为例[J]. 管理世界, 2019, (6): 109- 118 ZHAO Guanghui, LI Lingling The supervision of the new transport service business model in big data era: a case study of ride-hailing service[J]. Journal of Management World, 2019, (6): 109- 118 doi: 10.3969/j.issn.1002-5502.2019.06.010

[26]	LAI X, LIU Q, WANG W, et al Dynamic game with perfect and complete information based dynamic channel assignment[J]. Applied Intelligence, 2013, 39 (4): 692- 704 doi: 10.1007/s10489-012-0402-8

[27]	周忠宝, 任甜甜, 肖和录, 等资产收益序列相依下的多阶段投资博弈模型[J]. 管理科学学报, 2019, 22 (7): 66- 88 ZHOU Zhongbao, REN Tiantian, XIAO Helu, et al Multi-period portfolio game model with serially correlated returns[J]. Journal of Management Sciences in China, 2019, 22 (7): 66- 88 doi: 10.3969/j.issn.1007-9807.2019.07.005

[28]	罗掌华, 李亚坤, 冯力 “完全竞争”的一种理论思考[J]. 兰州学刊, 1996, (5): 34- 36 LUO Zhanghua, LI Yakun, FENG Li A theoretical reflection on “perfect competition”[J]. Lanzhou Academic Journal, 1996, (5): 34- 36

[29]	赵涛竞争优势与优势竞争: 后发地区的发展定位与竞争战略[J]. 经济问题探索, 2003, (4): 29- 35 ZHAO Tao To fixed competition advantage and advantage competition of development position and choice the competitive strategy in developing region[J]. Inquiry into Economic Issues, 2003, (4): 29- 35 doi: 10.3969/j.issn.1006-2912.2003.04.008

[30]	王京滨, 李博银行业务地理集中是否降低了金融风险? 基于中国城市商业银行微观数据的研究[J]. 管理世界, 2021, (5): 87- 97 WANG Jingbin, LI Bo Does the geographical concentration of banking business reduce financial risks? A study based on micro-level dataset of Chinese city commercial banks[J]. Journal of Management World, 2021, (5): 87- 97 doi: 10.3969/j.issn.1002-5502.2021.05.008

[31]	孙健, 宋茂星, 邱果, 等基于电动汽车大数据的多等级充电站选址及服务能力研究[J]. 中国公路学报, 2024, 37 (4): 48- 60 SUN Jian, SONG Maoxing, QIU Guo, et al Location and service capability of multilevel charging stations based on electric vehicle big data[J]. China Journal of Highway and Transport, 2024, 37 (4): 48- 60

[32]	LEI L C, GAO S, ZENG E Y Regulation strategies of ride-hailing market in China: an evolutionary game theoretic perspective[J]. Electronic Commerce Research, 2020, 20 (3): 535- 563 doi: 10.1007/s10660-020-09412-5

[33]	张群, 张卫国, 马勇中国金融市场系统复杂性的演化机理与管理研究[J]. 管理科学学报, 2017, 20 (1): 75- 86 ZHANG Qun, ZHANG Weiguo, MA Yong Evolution mechanisms and management of systemic complexity in China’s financial markets[J]. Journal of Management Sciences in China, 2017, 20 (1): 75- 86 doi: 10.3969/j.issn.1007-9807.2017.01.008

[34]	ARAÚJO J P C, OLIVEIRA J R M, SILVA H M R D The importance of the use phase on the LCA of environmentally friendly solutions for asphalt road pavements[J]. Transportation Research Part D: Transport and Environment, 2014, 32: 97- 110 doi: 10.1016/j.trd.2014.07.006

[35]	BERKOWICZ R, WINTHER M, KETZEL M Traffic pollution modelling and emission data[J]. Environmental Modelling and Software, 2006, 21 (4): 454- 460 doi: 10.1016/j.envsoft.2004.06.013

[36]	ZHANG S, WU Y, LIU H, et al Real-world fuel consumption and CO2 emissions of urban public buses in Beijing[J]. Applied Energy, 2014, 113: 1645- 1655 doi: 10.1016/j.apenergy.2013.09.017

[37]	邬彩霞中国低碳经济发展的协同效应研究[J]. 管理世界, 2021, (8): 105- 116 WU Caixia Research on the synergistic effect of low-carbon economy in China[J]. Journal of Management World, 2021, (8): 105- 116 doi: 10.3969/j.issn.1002-5502.2021.08.009

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