Choosing Networks for Ride-Hailing Platforms

Abstract

The development of autonomous vehicles is poised to reshape the landscape of transportation. As companies prepare to deploy these vehicles on ride-hailing platforms, a key operational challenge is determining the networks on which to train the vehicles. Our work contributes toward addressing this challenge on three fronts. First, we develop a theoretical model of the network selection problem and prove theoretical results that show the importance of two parameters: the detour factor and the fleet size. Second, we develop several approaches for selecting the networks. Third, we evaluate these approaches on empirical data. We find empirical support for the importance of the detour factor and the fleet size.