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Economic Assessment of Services with Intelligent Autonomous Vehicles: EASI-AV

In: The Robomobility Revolution of Urban Public Transport

Author

Listed:
  • Fabio Antonialli

    (École Centrale Lyon)

  • Sylvie Mira-Bonnardel

    (École Centrale Lyon)

  • Julie Bulteau

    (University of Paris-Saclay)

Abstract

While most of the current research on autonomous public transport focuses on improving operational and technical aspects, as well as tackling policy and user behavioral factors, the integration of autonomous buses into public networks is mainly dependent on costs and breakeven points (both for operators and local governments). Research quantifying costs and return on investment specifically in academic settings are sparse. This chapter aims to introduce a simulation tool: EASI-AV, designed as a decision-making tool to support public policies on the decision of implementing innovative mobility services. EASI-AV proposes to (1) assess the global economic impacts of deploying fleets of AVCTs in comparison with traditional public transport modes, and (2) help local authorities to build scenarios integrating autonomous buses into their public network and imagine new business models. The simulation is based on the Total Cost of Ownership (TCO) approach and includes four aspects that may be used independently: the fleet size dimensioning, the TCO calculation with internal costs and local externalities, the business model simulation, and the global impact assessment in comparison with other transport modes. EASI-AV was tested with real data from pilot sites, and the results prove it to be fully relevant.

Suggested Citation

  • Fabio Antonialli & Sylvie Mira-Bonnardel & Julie Bulteau, 2021. "Economic Assessment of Services with Intelligent Autonomous Vehicles: EASI-AV," Transportation Research, Economics and Policy, in: Sylvie Mira-Bonnardel & Fabio Antonialli & Danielle Attias (ed.), The Robomobility Revolution of Urban Public Transport, chapter 0, pages 85-105, Springer.
    • Handle: RePEc:spr:trachp:978-3-030-72976-9_4
    DOI: 10.1007/978-3-030-72976-9_4
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