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Robo-Taxi service fleet sizing: assessing the impact of user trust and willingness-to-use

Author

Listed:
  • Reza Vosooghi

    (Université Paris-Saclay
    Institut de Recherche Technologique SystemX)

  • Joseph Kamel

    (Institut de Recherche Technologique SystemX)

  • Jakob Puchinger

    (Université Paris-Saclay
    Institut de Recherche Technologique SystemX)

  • Vincent Leblond

    (Institut de Recherche Technologique SystemX)

  • Marija Jankovic

    (Université Paris-Saclay)

Abstract

The first commercial fleets of Robo-Taxis will be on the road soon. Today important efforts are made to anticipate future Robo-Taxi services. Fleet size is one of the key parameters considered in the planning phase of service design and configuration. Based on multi-agent approaches, the fleet size can be explored using dynamic demand response simulations. Time and cost are the most common variables considered in such simulation approaches. However, personal taste variation can affect the demand and consequently the required fleet size. In this paper, we explore the impact of user trust and willingness-to-use on the Robo-Taxi fleet size. This research is based upon simulating the transportation system of the Rouen-Normandie metropolitan area in France using MATSim, a multi-agent activity-based simulator. A local survey is made in order to explore the variation of user trust and their willingness-to-use future Robo-Taxis according to the sociodemographic attributes. Integrating survey data in the model shows the significant importance of traveler trust and willingness-to-use varying the Robo-Taxi use and the required fleet size.

Suggested Citation

  • Reza Vosooghi & Joseph Kamel & Jakob Puchinger & Vincent Leblond & Marija Jankovic, 2019. "Robo-Taxi service fleet sizing: assessing the impact of user trust and willingness-to-use," Transportation, Springer, vol. 46(6), pages 1997-2015, December.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:6:d:10.1007_s11116-019-10013-x
    DOI: 10.1007/s11116-019-10013-x
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    References listed on IDEAS

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    Cited by:

    1. Zhong, Yuanguang & Zillmann, Stefan & Zhang, Ruijie & Zhou, Yong-Wu & Xie, Wei, 2023. "Vehicle repositioning for a ride-sourcing network system providing differentiated services," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 221-243.
    2. May, Anthony D. & Shepherd, Simon & Pfaffenbichler, Paul & Emberger, Günter, 2020. "The potential impacts of automated cars on urban transport: An exploratory analysis," Transport Policy, Elsevier, vol. 98(C), pages 127-138.
    3. Mori, Kentaro & Miwa, Tomio & Abe, Ryosuke & Morikawa, Takayuki, 2022. "Equilibrium analysis of trip demand for autonomous taxi services in Nagoya, Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 476-498.
    4. Taha Benarbia & Kyandoghere Kyamakya & Fadi Al Machot & Witesyavwirwa Vianney Kambale, 2023. "Modeling and Simulation of Shared Electric Automated and Connected Mobility Systems with Autonomous Repositioning: Performance Evaluation and Deployment," Sustainability, MDPI, vol. 15(1), pages 1-23, January.
    5. Zwick, Felix & Kuehnel, Nico & Hörl, Sebastian, 2022. "Shifts in perspective: Operational aspects in (non-)autonomous ride-pooling simulations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 300-320.

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