Human-Driven, Autonomous, or Hybrid? The Optimal Fleet Configurations for Ride-Hailing Platforms

The growing commercialization of autonomous vehicles (AVs) is reshaping consumer service preferences and prompting ride-hailing platforms to redesign fleet structures that accommodate the coexistence of human-driven vehicles (HVs) and AVs. This article develops a queueing game framework that incorporates vehicle heterogeneity and consumer preference differences to systematically compare three fleet configuration strategies: the pure HV (PHV) strategy (HVs only), the pure AV (PAV) strategy (AVs only), and the hybrid strategy (both HVs and AVs). The analysis highlights how consumer mismatch losses, AV operating costs, and service rates jointly shape equilibrium outcomes. Results show that when consumer mismatch losses are moderate, the optimal fleet strategy transitions from PAV to hybrid as AV operating costs increase—and may even revert unexpectedly to a PHV configuration. From a multistakeholder perspective, when mismatch losses are high and AV operating costs are relatively low, the hybrid strategy can generate win–win–win outcomes for consumers, drivers, and platforms. Moreover, increasing either the HV or AV service rate improves platform profitability and can attract more consumers, although an excessively high HV service rate may depress driver wages. Robustness checks—incorporating heterogeneous driver opportunity costs and fixed AV deployment costs—confirm that the central insights hold across broader settings. Overall, the findings offer practical guidance for platform managers and policy-makers navigating the operational and strategic challenges of AV integration.