Competition among Ride Service Providers with Autonomous Vehicles

TL;DR

This paper models competition between autonomous vehicle ride service providers as a game, analyzing equilibrium strategies, market partitioning, and price dynamics in a multi-period network setting.

Contribution

It introduces a game-theoretic model for RSP competition with AVs, showing conditions for unique equilibrium and market partitioning effects.

Findings

Multiple Generalized Nash Equilibria can exist.

Potential function ensures a unique GNE under certain strategies.

Market partitioning occurs in low-demand inter-cluster networks.

Abstract

Autonomous vehicles (AVs) are attractive for ride service providers (RSPs) in part because they eliminate the need to compete for human drivers. We investigate a scenario where two RSPs with AVs compete for customers. We model the problem as a game where the RSPs select prices for each origin-destination pair over multiple time periods in an underlying graph representing the customers' desired trips. Each RSP also decides the number of AVs to be stationed at each node at each time period to serve the customers' demands. The number of customers who avail of the service of an RSP depends on the price selected by the RSP and its competitor. Since the strategy choices available to an RSP depends on its competitor, we seek to compute a Generalized Nash equilibrium (GNE). We show that there may be multiple GNEs. However, when an RSP selects prices in order to deter its competitor when it is not serving a source-destination pair, the game has a potential function and admits a unique GNE. We also compare the competitive prices with a monopoly price where only one RSP is in the market. Numerically, we show that if a network consists of two equal-size spatial clusters of demand where the demand between clusters is low, the RSPs may partition the market, i.e, one cluster is served by only one RSP. Hence, the competitive price may become close to the monopoly price.