IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v51y2024i5d10.1007_s11116-023-10391-3.html
   My bibliography  Save this article

A dynamic graph-based many-to-one ride-matching approach for shared autonomous electric vehicles

Author

Listed:
  • Ning Wang

    (Tongji University)

  • Yelin Lyu

    (Tongji University)

  • Shengling Jia

    (Tongji University)

  • Chaojun Zheng

    (State Grid Zhejiang Electric Vehicle Service Co., Ltd.)

  • Zhiquan Meng

    (State Grid Zhejiang Electric Vehicle Service Co., Ltd.)

  • Jingyun Chen

    (State Grid Zhejiang Electric Power Co., Ltd.)

Abstract

Shared autonomous electric vehicles (SAEVs) have recently attracted significant public interest. The dynamic ride-sharing using SAEVs appears to have the advantages of reducing travel costs and relieving urban traffic congestion. It is meant to improve the practical application value of the dynamic ride-sharing mode of SAEVs. In this paper, to reduce the solution time complexity, a pre-matching algorithm considering the driverless and charging characteristics of SAEVs is developed, and then a two-stage, graph-based many-to-one ride-matching (GMOM) algorithm is proposed for the dynamic ride-sharing problem in the Autonomous Mobility-on-Demand system (AMOD). The dataset from DiDi during the peak travel time and the real-time traffic flow from the AutoNavi map were used to verify the effects of the method. The results demonstrate that the GMOM approach can effectively reduce computational complexity and improve user satisfaction. The dynamic ride-sharing mode based on the GMOM algorithm has a 5.67% higher service rate and 45.56% more vehicle calls than the non-ride-sharing mode under the same conditions. It is found that the cost-effectiveness of using ride-sharing services is relatively high for 10–20 km trips during peak travel time and the dynamic ride-sharing may extend total travel time but will reduce passengers’ waiting time.

Suggested Citation

  • Ning Wang & Yelin Lyu & Shengling Jia & Chaojun Zheng & Zhiquan Meng & Jingyun Chen, 2024. "A dynamic graph-based many-to-one ride-matching approach for shared autonomous electric vehicles," Transportation, Springer, vol. 51(5), pages 1879-1905, October.
  • Handle: RePEc:kap:transp:v:51:y:2024:i:5:d:10.1007_s11116-023-10391-3
    DOI: 10.1007/s11116-023-10391-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-023-10391-3
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-023-10391-3?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. Kiviluoma, Juha & Meibom, Peter, 2011. "Methodology for modelling plug-in electric vehicles in the power system and cost estimates for a system with either smart or dumb electric vehicles," Energy, Elsevier, vol. 36(3), pages 1758-1767.
    2. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
    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. Masoud, Neda & Jayakrishnan, R., 2017. "A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 1-29.
    5. Liu, Mengyang & Luo, Zhixing & Lim, Andrew, 2015. "A branch-and-cut algorithm for a realistic dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 267-288.
    6. 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).
    7. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    8. de Palma, André & Stokkink, Patrick & Geroliminis, Nikolas, 2022. "Influence of dynamic congestion with scheduling preferences on carpooling matching with heterogeneous users," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 479-498.
    9. Furuhata, Masabumi & Dessouky, Maged & Ordóñez, Fernando & Brunet, Marc-Etienne & Wang, Xiaoqing & Koenig, Sven, 2013. "Ridesharing: The state-of-the-art and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 28-46.
    10. Bongiovanni, Claudia & Kaspi, Mor & Geroliminis, Nikolas, 2019. "The electric autonomous dial-a-ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 436-456.
    11. Masoud, Neda & Lloret-Batlle, Roger & Jayakrishnan, R., 2017. "Using bilateral trading to increase ridership and user permanence in ridesharing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 60-77.
    Full references (including those not matched with items on IDEAS)

    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. Hua, Shijia & Zeng, Wenjia & Liu, Xinglu & Qi, Mingyao, 2022. "Optimality-guaranteed algorithms on the dynamic shared-taxi problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Horner, Hannah & Pazour, Jennifer & Mitchell, John E., 2021. "Optimizing driver menus under stochastic selection behavior for ridesharing and crowdsourced delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    3. 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).
    4. Bian, Zheyong & Liu, Xiang & Bai, Yun, 2020. "Mechanism design for on-demand first-mile ridesharing," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 77-117.
    5. Lei, Chao & Jiang, Zhoutong & Ouyang, Yanfeng, 2020. "Path-based dynamic pricing for vehicle allocation in ridesharing systems with fully compliant drivers," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 60-75.
    6. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part I: Theoretical analysis in generalized scenarios," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 147-171.
    7. Qing-Long Lu & Moeid Qurashi & Constantinos Antoniou, 2024. "A ridesplitting market equilibrium model with utility-based compensation pricing," Transportation, Springer, vol. 51(2), pages 439-474, April.
    8. 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.
    9. Sun, Yanshuo & Chen, Zhi-Long & Zhang, Lei, 2020. "Nonprofit peer-to-peer ridesharing optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    10. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem & Yacine Rekik, 2022. "Environmental and social implications of incorporating carpooling service on a customized bus system," Post-Print hal-03598768, HAL.
    11. Zhang, Ruolin & Masoud, Neda, 2021. "A distributed algorithm for operating large-scale ridesourcing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    12. 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.
    13. Daganzo, Carlos F. & Ouyang, Yanfeng, 2019. "A general model of demand-responsive transportation services: From taxi to ridesharing to dial-a-ride," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 213-224.
    14. Meng Li & Guowei Hua & Haijun Huang, 2018. "A Multi-Modal Route Choice Model with Ridesharing and Public Transit," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    15. Tafreshian, Amirmahdi & Masoud, Neda, 2022. "A truthful subsidy scheme for a peer-to-peer ridesharing market with incomplete information," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 130-161.
    16. Qin, Hu & Moriakin, Anton & Xu, Gangyan & Li, Jiliu, 2024. "The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach," European Journal of Operational Research, Elsevier, vol. 318(3), pages 752-767.
    17. Daganzo, Carlos F. & Ouyang, Yanfeng & Yang, Haolin, 2020. "Analysis of ride-sharing with service time and detour guarantees," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 130-150.
    18. Fan, Wenbo & Gu, Weihua & Xu, Meng, 2024. "Optimal design of ride-pooling as on-demand feeder services," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    19. Zhong, Lin & Zhang, Kenan & (Marco) Nie, Yu & Xu, Jiuping, 2020. "Dynamic carpool in morning commute: Role of high-occupancy-vehicle (HOV) and high-occupancy-toll (HOT) lanes," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 98-119.
    20. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part II: Solution algorithm for large-scale problems," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 172-192.

    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:kap:transp:v:51:y:2024:i:5:d:10.1007_s11116-023-10391-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.