Competition in Electric Autonomous Mobility on Demand Systems

TL;DR

This paper analyzes how competition affects autonomous mobility-on-demand systems, focusing on optimal pricing, profits, and consumer surplus in monopoly and duopoly markets using a network-flow model.

Contribution

It introduces a network-flow based framework to determine optimal strategies and theoretical bounds for profits, prices, and consumer surplus under different market structures.

Findings

Symmetric equilibrium prices in duopoly markets.

Universal bounds on price ratios, demand, profits, and consumer surplus.

Static and real-time policies' efficacy evaluated with real data.

Abstract

This paper investigates the impacts of competition in autonomous mobility-on-demand systems. By adopting a network-flow based formulation, we first determine the optimal strategies of profit-maximizing platform operators in monopoly and duopoly markets, including the optimal prices of rides. Furthermore, we characterize the platform operator's profits and the consumer surplus. We show that for the duopoly, the equilibrium prices for rides have to be symmetric between the firms. Then, in order to study the benefits of introducing competition in the market, we derive universal theoretical bounds on the ratio of prices for rides, aggregate demand served, profits of the firms, and consumer surplus between the monopolistic and the duopolistic setting. We discuss how consumers' firm loyalty affects each of the aforementioned metrics. Finally, using the Manhattan network and demand data, we quantify the efficacy of static pricing and routing policies and compare it to real-time model predictive policies.