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Fleet Sizing Models for Demand-Responsive Transport: A Simplified Approach for Practical Implementation

In: Customizing Public Transport

Author

Listed:
  • Alexandre Lefort

    (E-Cole)

Abstract

This chapter examines one of the main challenges in demand-responsive transport (DRT): determining the optimal fleet size that balances service quality with economic sustainability. Fleet sizing in on-demand systems is more complex than in fixed-route transit, as demand varies across time and space. The chapter introduces a simplified yet comprehensive model that supports decision-making without requiring advanced optimization tools. It is designed for transport operators, particularly in smaller cities or emerging markets, who need practical methods for planning. The model integrates key parameters such as trip length, vehicle speed, operating hours, demand fluctuations, and service quality indicators like waiting time and acceptable delay. It conceptualizes the service area as a circular zone to simplify the estimation of coverage and deviation times when vehicles pick up passengers outside their routes. This geometric framework offers sufficient accuracy for preliminary planning while remaining accessible to nonspecialists. By incorporating demand density and analyzing the trade-off between responsiveness and efficiency, the model estimates realistic service times and fleet requirements. Case studies from Mediterranean cities demonstrate its adaptability and highlight how area size, demand intensity, and quality standards shape fleet needs. The chapter concludes with guidelines for calibration and sensitivity analysis to tailor the model to diverse operational contexts.

Suggested Citation

  • Alexandre Lefort, 2026. "Fleet Sizing Models for Demand-Responsive Transport: A Simplified Approach for Practical Implementation," Transportation Research, Economics and Policy, in: Fabio Antonialli & Sylvie Mira-Bonnardel (ed.), Customizing Public Transport, chapter 4, pages 51-71, Springer.
  • Handle: RePEc:spr:trachp:978-3-032-22295-4_4
    DOI: 10.1007/978-3-032-22295-4_4
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