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Mobile phone GPS data in urban ride-sharing: An assessment method for emission reduction potential

Author

Listed:
  • Zhang, Haoran
  • Chen, Jinyu
  • Li, Wenjing
  • Song, Xuan
  • Shibasaki, Ryosuke

Abstract

Spreading green and low-consumption transportation methods is becoming an urgent priority. Ride-sharing, which refers to the sharing ofcarjourneys so that more than one person travel in a car, and prevents the need for others to drive to a location themselves, is a critical solution to this issue. Before being introduced into one place, it needs a potential analysis. However, current studies did this kind of analysis based on home and work locations or social ties between people, which is not precise and straight enough. Few pieces of research departed from real mobility data, but uses time-consuming methodology. In this paper, we proposed an analysis framework to bridge this gap. We chose the case study of Tokyo area with over 1 million GPS travel records and trained a deep learning model to find out this potential. From the computation result, on average, nearly 26.97% of travel distance could be saved by ride-sharing, which told us that there is a significant similarity in the travel pattern of people in Tokyo and there is considerable potential of ride-sharing. Moreover, if half of the original public transit riders in our study case adopt ride-sharing, the quantity of CO2 is estimated to be reduced by 84.52%; if all of the original public transit riders in our study case adopt ride-sharing, 83.56% of CO2 emission reduction can be expected with a rebound effect because of increase of participants from public transit. Ride-sharing can not only improve the air quality of these center business districts but also alleviate some city problems like traffic congestion. We believe the analysis of the potential of ride-sharing can provide insight into the decision making of ride-sharing service providers and decision-makers.

Suggested Citation

  • Zhang, Haoran & Chen, Jinyu & Li, Wenjing & Song, Xuan & Shibasaki, Ryosuke, 2020. "Mobile phone GPS data in urban ride-sharing: An assessment method for emission reduction potential," Applied Energy, Elsevier, vol. 269(C).
  • Handle: RePEc:eee:appene:v:269:y:2020:i:c:s030626192030550x
    DOI: 10.1016/j.apenergy.2020.115038
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    References listed on IDEAS

    as
    1. Yu, Biying & Ma, Ye & Xue, Meimei & Tang, Baojun & Wang, Bin & Yan, Jinyue & Wei, Yi-Ming, 2017. "Environmental benefits from ridesharing: A case of Beijing," Applied Energy, Elsevier, vol. 191(C), pages 141-152.
    2. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    3. Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.
    4. Roozbeh Jalali & Seama Koohi-Fayegh & Khalil El-Khatib & Daniel Hoornweg & Heng Li, 2017. "Investigating the Potential of Ridesharing to Reduce Vehicle Emissions," Urban Planning, Cogitatio Press, vol. 2(2), pages 26-40.
    5. Zhang, Haoran & Song, Xuan & Xia, Tianqi & Yuan, Meng & Fan, Zipei & Shibasaki, Ryosuke & Liang, Yongtu, 2018. "Battery electric vehicles in Japan: Human mobile behavior based adoption potential analysis and policy target response," Applied Energy, Elsevier, vol. 220(C), pages 527-535.
    6. Tsao, H.-S. Jacob & Lin, Da-Jie, 1999. "Spatial and Temporal Factors in Estimating the Potential of Ride-sharing for Demand Reduction," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2p57q0c9, Institute of Transportation Studies, UC Berkeley.
    7. Guowei Zhu & Hongshan Li & Li Zhou, 2018. "Enhancing the development of sharing economy to mitigate the carbon emission: a case study of online ride-hailing development in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 611-633, March.
    8. Sun, Hao & Wang, Hai & Wan, Zhixi, 2019. "Model and analysis of labor supply for ride-sharing platforms in the presence of sample self-selection and endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 76-93.
    9. Li, Peilin & Zhao, Pengjun & Brand, Christian, 2018. "Future energy use and CO2 emissions of urban passenger transport in China: A travel behavior and urban form based approach," Applied Energy, Elsevier, vol. 211(C), pages 820-842.
    10. Meng, Fanxin & Liu, Gengyuan & Yang, Zhifeng & Casazza, Marco & Cui, Shenghui & Ulgiati, Sergio, 2017. "Energy efficiency of urban transportation system in Xiamen, China. An integrated approach," Applied Energy, Elsevier, vol. 186(P2), pages 234-248.
    11. Agatz, Niels A.H. & Erera, Alan L. & Savelsbergh, Martin W.P. & Wang, Xing, 2011. "Dynamic ride-sharing: A simulation study in metro Atlanta," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1450-1464.
    12. Sun, Lishan & Wang, Shunchao & Liu, Shuli & Yao, Liya & Luo, Wei & Shukla, Ashish, 2018. "A completive research on the feasibility and adaptation of shared transportation in mega-cities – A case study in Beijing," Applied Energy, Elsevier, vol. 230(C), pages 1014-1033.
    13. Liu, Xiaobing & Yan, Xuedong & Liu, Feng & Wang, Rui & Leng, Yan, 2019. "A trip-specific model for fuel saving estimation and subsidy policy making of carpooling based on empirical data," Applied Energy, Elsevier, vol. 240(C), pages 295-311.
    14. Zhang, Haoran & Song, Xuan & Long, Yin & Xia, Tianqi & Fang, Kai & Zheng, Jianqin & Huang, Dou & Shibasaki, Ryosuke & Liang, Yongtu, 2019. "Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis," Applied Energy, Elsevier, vol. 242(C), pages 138-147.
    15. Biao Yin & Liu Liu & Nicolas Coulombel & Vincent Viguie, 2018. "Appraising the environmental benefits of ride-sharing: The Paris region case study," Post-Print hal-01695082, HAL.
    16. Timm Teubner & Christoph Flath, 2015. "The Economics of Multi-Hop Ride Sharing," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(5), pages 311-324, October.
    17. Naoum-Sawaya, Joe & Cogill, Randy & Ghaddar, Bissan & Sajja, Shravan & Shorten, Robert & Taheri, Nicole & Tommasi, Pierpaolo & Verago, Rudi & Wirth, Fabian, 2015. "Stochastic optimization approach for the car placement problem in ridesharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 173-184.
    18. Long, Jiancheng & Tan, Weimin & Szeto, W.Y. & Li, Yao, 2018. "Ride-sharing with travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 143-171.
    19. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
    20. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    21. Hai-Jun Huang & Hai Yang & Michael G.H. Bell, 2000. "The models and economics of carpools," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 34(1), pages 55-68.
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    Cited by:

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