A bi-level framework for heterogeneous fleet sizing of ride-hailing services considering an approximated mixed equilibrium between automated and non-automated traffic

Qiaochu Fan*, J. Theresia van Essen, Gonçalo H.A. Correia

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Ride-hailing companies will face the emergence and gradual expansion of AVs-only zones in urban areas where only automated vehicles (AVs) are allowed to circulate. When owning a mixed fleet (automated and conventional taxis), a ride-hailing company has to determine the optimal fleet size as a function of the gradually expanding coverage of AVs-only zones while taking into account interactions with privately-owned human-driven vehicles. To model this problem, we propose a bi-level framework in which the lower level captures the mixed routing behaviour of the vehicles and the endogenous traffic congestion, and the upper level determines fleet sizes to maximise profit. A parallel genetic algorithm is introduced to solve this bi-level framework, which is embedded with a tailored algorithm for solving the lower-level model. Numerical experiments are conducted on instances based on a small network and the network of the city of Delft, The Netherlands, to demonstrate the performance of the proposed solution method and investigate the impacts of AVs-only zones on traffic and ride-hailing operations. Results indicate that the fleet size of automated taxis increases nonlinearly with the expansion of the AVs-only zone while that of conventional taxis decreases as demand shifts from human-driven vehicles to automated taxis. The fleet size decision depends heavily on the fleet's cost structure, the location and the distribution of parking depots. Furthermore, the existence of an AVs-only zone leads to detours for human-driven vehicles in the early stages, but it will bring major benefits by reducing congestion as its size increases.

Original languageEnglish
Number of pages20
JournalEuropean Journal of Operational Research
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Routing
  • Fleet sizing
  • Approximated mixed equilibrium
  • AVs-only zone
  • e-hailing services

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