TRIMP: Three-Sided Stable Matching for Distributed Vehicle Sharing System Using Stackelberg Game

Yang Xu, Shanshan Zhang, Chen Lyu, Jia Liu, Tarik Taleb, Norio Shiratori

Abstract: Distributed Vehicle Sharing System (DVSS) leverages emerging technologies such as blockchain to create a secure, transparent, and efficient platform for sharing vehicles. In such a system, both efficient matching of users with available vehicles and optimal pricing mechanisms play crucial roles in maximizing system revenue. However, most existing schemes utilize user-to-vehicle (two-sided) matching and pricing, which are unrealistic for DVSS due to the lack of participation of service providers. To address this issue, we propose in this paper a novel Three-sided stable Matching with an optimal Pricing (TRIMP) scheme. First, to achieve maximum utilities for all three parties simultaneously, we formulate the optimal policy and pricing problem as a three-stage Stackelberg game and derive its equilibrium points accordingly. Second, relying on these solutions from the Stackelberg game, we construct a three-sided cyclic matching for DVSS. Third, as the existence of such a matching is NP-complete, we design a specific vehicle sharing algorithm to realize stable matching. Extensive experiments demonstrate the effectiveness of our TRIMP scheme, which optimizes the matching process and ensures efficient resource allocation, leading to a more stable and well-functioning decentralized vehicle sharing ecosystem.