IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v156y2022icp206-226.html
   My bibliography  Save this article

Effects and feasibility of shared mobility with shared autonomous vehicles: An investigation based on data-driven modeling approach

Author

Listed:
  • Liu, Zhiyong
  • Li, Ruimin
  • Dai, Jingchen

Abstract

Shared mobility is a promising travel mode in the era of autonomous driving. Travelers may no longer own a vehicle, but use shared autonomous vehicle (SAV) services. This study investigates the effects and feasibility of SAV-based shared mobility, which includes ride-sharing and car-sharing strategies, by using a data-driven modeling approach. Ride-sharing indicates that two trips with similar origin–destination information can be combined into a new one, whereas car-sharing indicates that trips can be fulfilled by a single vehicle consecutively. On the basis of license plate recognition data of Langfang, China, this study extracts the urban-scale vehicle travel demand information. Models for ride-sharing and car-sharing are formulated to generate SAV assignment strategies for fulfilling travel demands. This study reveals the prospects and potential problems of SAV-supported shared mobility at different development stages by setting a variety of scenarios with different participation levels of ride-sharing and car-sharing. The minimum fleet size to fulfil the vehicle travel demand in the road network and the total vehicle stock in the urban area are compared under different scenarios, and the effects of shared mobility on vehicle kilometers traveled (VKT) and parking demand are evaluated. This study also reveals the impacts of SAVs in a practical scenario, which is constructed based on an online survey. Results show that ride-sharing and car-sharing with high participation will lead to considerable benefits, i.e., reductions in fleet size, vehicle stock, and parking demand. Under the shared mobility scenario with 100% ride-sharing and car-sharing participation levels, one SAV can potentially replace 3.80 private conventional vehicles in the road network. However, ride-sharing and car-sharing exhibit opposite effects on VKT. Car-sharing alone increases VKT whereas car-sharing and ride-sharing together have the potential to decrease VKT. This study provides insights for understanding the development of shared mobility and facilitating the efficient utilization of SAVs.

Suggested Citation

  • Liu, Zhiyong & Li, Ruimin & Dai, Jingchen, 2022. "Effects and feasibility of shared mobility with shared autonomous vehicles: An investigation based on data-driven modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 206-226.
  • Handle: RePEc:eee:transa:v:156:y:2022:i:c:p:206-226
    DOI: 10.1016/j.tra.2022.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422000015
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2022.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Inturri, Giuseppe & Le Pira, Michela & Giuffrida, Nadia & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea & D'Angelo, Riccardo, 2019. "Multi-agent simulation for planning and designing new shared mobility services," Research in Transportation Economics, Elsevier, vol. 73(C), pages 34-44.
    2. Xing Wang & Niels Agatz & Alan Erera, 2018. "Stable Matching for Dynamic Ride-Sharing Systems," Transportation Science, INFORMS, vol. 52(4), pages 850-867, August.
    3. Daniel J. Fagnant & Kara M. Kockelman, 2018. "Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas," Transportation, Springer, vol. 45(1), pages 143-158, January.
    4. Shaheen, Susan & Cohen, Adam & Zohdy, Ismail & Kock, Beaudry, 2016. "Smartphone Applications to Influence Travel Choices: Practices and Policies," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8dq801g7, Institute of Transportation Studies, UC Berkeley.
    5. Hyland, Michael & Mahmassani, Hani S., 2020. "Operational benefits and challenges of shared-ride automated mobility-on-demand services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 251-270.
    6. Greenblatt, Jeffery & Shaheen, Susan PhD, 2015. "Automated Vehicles, On-Demand Mobility and Environmental Impacts," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt23r1h80t, Institute of Transportation Studies, UC Berkeley.
    7. Ho, Sin C. & Szeto, W.Y. & Kuo, Yong-Hong & Leung, Janny M.Y. & Petering, Matthew & Tou, Terence W.H., 2018. "A survey of dial-a-ride problems: Literature review and recent developments," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 395-421.
    8. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
    9. Rodier, Caroline & Alemi, Farzad & Smith, Dylan, 2016. "Dynamic Ridesharing: Exploration of Potential for Reduction in Vehicle Miles Traveled," Institute of Transportation Studies, Working Paper Series qt6r6139g8, Institute of Transportation Studies, UC Davis.
    10. Chen, T. Donna & Kockelman, Kara M. & Hanna, Josiah P., 2016. "Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 243-254.
    11. Hosni, Hadi & Naoum-Sawaya, Joe & Artail, Hassan, 2014. "The shared-taxi problem: Formulation and solution methods," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 303-318.
    12. Abrahamse, Wokje & Keall, Michael, 2012. "Effectiveness of a web-based intervention to encourage carpooling to work: A case study of Wellington, New Zealand," Transport Policy, Elsevier, vol. 21(C), pages 45-51.
    13. Braekers, Kris & Kovacs, Attila A., 2016. "A multi-period dial-a-ride problem with driver consistency," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 355-377.
    14. Becker, Henrik & Balac, Milos & Ciari, Francesco & Axhausen, Kay W., 2020. "Assessing the welfare impacts of Shared Mobility and Mobility as a Service (MaaS)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 228-243.
    15. Mounce, Richard & Nelson, John D., 2019. "On the potential for one-way electric vehicle car-sharing in future mobility systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 17-30.
    16. 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.
    17. M. M. Vazifeh & P. Santi & G. Resta & S. H. Strogatz & C. Ratti, 2018. "Addressing the minimum fleet problem in on-demand urban mobility," Nature, Nature, vol. 557(7706), pages 534-538, May.
    18. Kaddoura, Ihab & Bischoff, Joschka & Nagel, Kai, 2020. "Towards welfare optimal operation of innovative mobility concepts: External cost pricing in a world of shared autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 48-63.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin Tu & Min Xu, 2024. "An Analysis of the Use of Autonomous Vehicles in the Shared Mobility Market: Opportunities and Challenges," Sustainability, MDPI, vol. 16(16), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Ke, Jintao & Yang, Hai & Li, Xinwei & Wang, Hai & Ye, Jieping, 2020. "Pricing and equilibrium in on-demand ride-pooling markets," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 411-431.
    3. Johnsen, Lennart C. & Meisel, Frank, 2022. "Interrelated trips in the rural dial-a-ride problem with autonomous vehicles," European Journal of Operational Research, Elsevier, vol. 303(1), pages 201-219.
    4. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2022. "Dynamic ride-sharing impacts of greater trip demand and aggregation at stops in shared autonomous vehicle systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 114-125.
    5. Wang, Jun & Wang, Xiaolei & Yang, Shan & Yang, Hai & Zhang, Xiaoning & Gao, Ziyou, 2021. "Predicting the matching probability and the expected ride/shared distance for each dynamic ridepooling order: A mathematical modeling approach," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 125-146.
    6. Hyland, Michael & Mahmassani, Hani S., 2020. "Operational benefits and challenges of shared-ride automated mobility-on-demand services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 251-270.
    7. María J. Alonso-González & Oded Cats & Niels van Oort & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 2021. "What are the determinants of the willingness to share rides in pooled on-demand services?," Transportation, Springer, vol. 48(4), pages 1733-1765, August.
    8. Li, Yuanyuan & Liu, Yang, 2021. "Optimizing flexible one-to-two matching in ride-hailing systems with boundedly rational users," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    9. María J. Alonso-González & Oded Cats & Niels van Oort & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 0. "What are the determinants of the willingness to share rides in pooled on-demand services?," Transportation, Springer, vol. 0, pages 1-33.
    10. Yi, Xu & Lian, Feng & Yang, Zhongzhen, 2022. "Research on commuters’ carpooling behavior in the mobile internet context," Transport Policy, Elsevier, vol. 126(C), pages 14-25.
    11. Noruzoliaee, Mohamadhossein & Zou, Bo, 2022. "One-to-many matching and section-based formulation of autonomous ridesharing equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 72-100.
    12. Ke, Jintao & Yang, Hai & Zheng, Zhengfei, 2020. "On ride-pooling and traffic congestion," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 213-231.
    13. Guo, Jiaqi & Long, Jiancheng & Xu, Xiaoming & Yu, Miao & Yuan, Kai, 2022. "The vehicle routing problem of intercity ride-sharing between two cities," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 113-139.
    14. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2020. "Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    15. Fielbaum, Andrés & Tirachini, Alejandro & Alonso-Mora, Javier, 2023. "Economies and diseconomies of scale in on-demand ridepooling systems," Economics of Transportation, Elsevier, vol. 34(C).
    16. Andres Fielbaum & Maximilian Kronmueller & Javier Alonso-Mora, 2022. "Anticipatory routing methods for an on-demand ridepooling mobility system," Transportation, Springer, vol. 49(6), pages 1921-1962, December.
    17. Krueger, Rico & Rashidi, Taha H. & Vij, Akshay, 2020. "A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles," Journal of choice modelling, Elsevier, vol. 36(C).
    18. Zhang, Li & Liu, Zhongshan & Yu, Lan & Fang, Ke & Yao, Baozhen & Yu, Bin, 2022. "Routing optimization of shared autonomous electric vehicles under uncertain travel time and uncertain service time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    19. Soria, Jason & Stathopoulos, Amanda, 2021. "Investigating socio-spatial differences between solo ridehailing and pooled rides in diverse communities," Journal of Transport Geography, Elsevier, vol. 95(C).
    20. Zhen, Lu & Tan, Zheyi & Wang, Shuaian & Yi, Wen & Lyu, Junyan, 2021. "Shared mobility oriented open vehicle routing with order radius decision," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 19-33.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:156:y:2022:i:c:p:206-226. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.