Simulating the Ridesharing Economy: The Individual Agent Metro-Washington Area Ridesharing Model.

The ridesharing economy is experiencing rapid growth and innovation.Companies such as Uber and Lyft are continuing to grow at a considerable pacewhile providing their platform as an organizing medium for ridesharingservices, increasing consumer utility as well as employing thousands inpart-time positions. However, many challenges remain in the modeling ofridesharing services, many of which are not currently under wide consideration.In this paper, an agent-based model is developed to simulate a ridesharingservice in the Washington D.C. metropolitan region. The model is used toexamine levels of utility gained for both riders (customers) and drivers(service providers) of a generic ridesharing service. A description of theIndividual Agent Metro-Washington Area Ridesharing Model (IAMWARM) is provided,as well as a description of a typical simulation run. We investigate thefinancial gains of drivers for a 24-hour period under two scenarios and twospatial movement behaviors. The two spatial behaviors were random movement andVoronoi movement, which we describe. Both movement behaviors were tested undera stationary run conditions scenario and a variable run conditions scenario. Wefind that Voronoi movement increased drivers' utility gained but that emergenceof this system property was only viable under variable scenario conditions.This result provides two important insights: The first is that driver movementdecisions prior to passenger pickup can impact financial gain for the serviceand drivers, and consequently, rate of successful pickup for riders. The secondis that this phenomenon is only evident under experimentation conditions wherevariability in passenger and driver arrival rates are administered.