Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles

TL;DR

This paper develops an equilibrium model to analyze the market for autonomous vehicle rentals used for on-demand ride services, revealing profitability, welfare impacts, and optimal pricing strategies.

Contribution

It introduces a comprehensive aggregate equilibrium framework for AV crowdsourcing markets, incorporating customer choices, congestion effects, and profit/social welfare optimization.

Findings

Crowdsourcing can enhance welfare and profitability.

Small-scale crowdsourcing may be unprofitable without intervention.

A second-best pricing scheme can prevent unprofitable scenarios.

Abstract

Autonomous vehicles (AVs) have the potential of reshaping the human mobility in a wide variety of aspects. This paper focuses on a new possibility that the AV owners have the option of "renting" their AVs to a company, which can use these collected AVs to provide on-demand ride services without any drivers. We call such a mobility market with AV renting options the "AV crowdsourcing market". This paper establishes an aggregate equilibrium model with multiple transport modes to analyze the AV crowdsourcing market. The modeling framework can capture the customers' mode choices and AV owners' rental decisions with the presence of traffic congestion. Then, we explore different scenarios that either maximize the crowdsourcing platform's profit or maximize social welfare. Gradient-based optimization algorithms are designed for solving the problems. The results obtained by numerical examples reveal the welfare enhancement and the strong profitability of the AV crowdsourcing service. However, when the crowdsourcing scale is small, the crowdsourcing platform might not be profitable. A second-best pricing scheme is able to avoid such undesirable cases. The insights generated from the analyses provide guidance for regulators, service providers and citizens to make future decisions regarding the utilization of the AV crowdsourcing markets for serving the good of the society.