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

  • Reza VosooghiEmail author
  • Joseph Kamel
  • Jakob Puchinger
  • Vincent Leblond
  • Marija Jankovic


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.


Multi-agent simulation Shared autonomous vehicle Robo-Taxi Willingness-to-use User trust Fleet size 



This research work has been carried out in the framework of IRT SystemX, Paris-Saclay, France, and therefore granted with public funds within the scope of the French Program “Investissements d’Avenir”. The authors would like to thank Groupe Renault for partially financing this work and Métropole Rouen-Normandie for providing the data.

Author contribution

The authors confirm contribution to the paper as follows: study conception and design: R. Vosooghi, J. Puchinger, M. Jankovic; transport survey and data collection: Groupe Renault, Métropole Rouen Normandie; user survey: R. Vosooghi, J. Puchinger and other contributors; analysis and interpretation of results: R. Vosooghi, J. Kamel, J. Puchinger, V. Leblond; draft manuscript preparation: R. Vosooghi. All authors reviewed the results and approved the final version of the manuscript.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratoire Génie Industriel, CentraleSupelécUniversité Paris-SaclayGif-sur-YvetteFrance
  2. 2.Institut de Recherche Technologique SystemXPalaiseauFrance

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