Receding-Horizon Games with Tullock-Based Profit Functions for Electric Ride-Hailing Markets

TL;DR

This paper introduces a receding-horizon game-theoretic approach for electric ride-hailing charging strategies, incorporating a modified Tullock contest to model market share and demand-based electricity costs, with proven equilibrium properties.

Contribution

It develops a novel receding-horizon game framework with a Tullock-based profit function, addressing dynamic demand, energy costs, and competition in electric ride-hailing markets.

Findings

Existence and uniqueness of Nash equilibrium established.

Semi-decentralized iterative method for equilibrium computation.

Method validated through numerical simulations.

Abstract

This paper proposes a receding-horizon, game-theoretic charging planning mechanism for electric ride-hailing markets. As the demand for ride-hailing services continues to surge and governments advocate for stricter environmental regulations, integrating electric vehicles into these markets becomes inevitable. The proposed framework addresses the challenges posed by dynamic demand patterns, fluctuating energy costs, and competitive dynamics inherent in such markets. Leveraging the concept of receding-horizon games, we propose a method to optimize proactive dispatching of vehicles for recharging over a predefined time horizon. We integrate a modified Tullock contest that accounts for customer abandonment due to long waiting times to model the expected market share, and by factoring in the demand-based electricity charging, we construct a game capturing interactions between two companies over the time horizon. For this game, we first establish the existence and uniqueness of the Nash equilibrium and then present a semi-decentralized, iterative method to compute it. Finally, the method is evaluated in an open-loop and a closed-loop manner in a simulated numerical case study.