Detours in Shared Rides

Abstract

Detours are considered key for the efficient operation of a shared rides service, but are also the major pain point for consumers of such services. This paper studies the relationship between the value generated by shared rides and the detours they create for riders. We establish a fundamental limit on the sum of value and detour, and prove this leads to a tight bound on the Pareto frontier of values and detours in a general setting with an arbitrary number requests. We explicitly compute the Pareto frontier for one family of city topologies, and construct it via simulation for several more networks, including one based on ridesharing data from commute hours in Manhattan. We find that average detours are surprisingly small even in low demand density settings. We also find that by carefully choosing the match objective, detours can be significantly reduced with little impact on value, and that the density of ride requests is far more important than detours for the effective operations of a shared rides service. In response to these findings, we propose that platforms implement a two-product version of a shared rides service.