Priority matching with cost consideration for ride-hailingservices

In a ride-hailing platform, assignment of drivers to passengers is handled as a resource allocation problem. From the point of view of the platform, drivers and passengers both are customers. In different business domains customer prioritization is applied to enhance customer experience. We apply priority structures for a ride-hailing platform and propose related matching procedures. Given predefined priority ordering of the agents the goal of this study is to develop methods to find priority matchings while also considering the total cost of assignment. Due to complexity of the assignment process for a ride-hailing service, performance of the proposed procedures is experimentally observed in a simulation environment with an artificial data. Assumptions on the distribution of demand and supply are made based on the analysis of open source data of New York City taxi rides. Defining both the passengers and drivers as customers, priority structure and proposed procedures are applied to the both sides. The effect of incremental saturation of priority agents on the average pick up distance is revealed under various scenarios such as insufficient, balanced or excess supply and different ratios of priority passengers or priority drivers. In order to provide insights for decision makers, the price of priority consideration is investigated using various performance metrics such as average pick up distance and the ratio of successfully completed rides.