To Collaborate or Not: The Autonomous Vehicles Introduction Strategy of the Traditional Ride-Hailing Platform
Year: 2025
Type: article
Abstract: Autonomous ride-hailing services, as an innovative solution in the shared mobility sector, have sparked intense competition with traditional ride-hailing platforms. This study examines a traditional large-scale ride-hailing platform and an autonomous ride-hailing platform, constructing profit models for both platforms under competitive and cooperative scenarios. The impact of these scenarios on the platforms’ optimal profits is analyzed using a game-theoretic framework. The study identifies passenger trust in the autonomous platform and the commission rate as critical factors influencing the strategic choices of the two platforms. Surprisingly, irrespective of variations in passenger valuation coefficients and commission rates, there is no scenario where both platforms simultaneously prefer cooperation, which contradicts intuitive expectations. Furthermore, the findings suggest that when passenger trust and valuation differences are relatively low, the autonomous platform can maximize profits by adopting a high-pricing strategy. However, as passenger trust and valuation differences increase, the autonomous platform must adjust its strategy, shifting toward cost optimization and price competition. The study also explores the role of transfer payments as an incentive mechanism for traditional platforms to encourage cooperation from autonomous platforms, providing a robust theoretical foundation for fostering collaboration between traditional and autonomous ride-hailing platforms.
Source: Systems
Authors: Linlin Fan, Min Guo
Institution: North University of China
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4408778792