Book-Ahead & Supply Management for Ridesourcing Platforms
| Autor: | Gustavo de Veciana, Michael Stecklein, Jean Abou Rahal, Stephen D. Boyles, Cesar N. Yahia |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Service (business)
050210 logistics & transportation Schedule 021103 operations research Operations research Computer science Quality of service 05 social sciences 0211 other engineering and technologies Transportation Systems and Control (eess.SY) 02 engineering and technology Admission control Variation (game tree) Management Science and Operations Research Electrical Engineering and Systems Science - Systems and Control Supply management 11. Sustainability 0502 economics and business Automotive Engineering FOS: Electrical engineering electronic engineering information engineering TRIPS architecture Start time Civil and Structural Engineering |
| Popis: | Ridesourcing platforms recently introduced the “schedule a ride” service where passengers may reserve (book-ahead) a ride in advance of their trip. Reservations give platforms precise information that describes the start time and location of anticipated future trips; in turn, platforms can use this information to adjust the availability and spatial distribution of the driver supply. In this article, we propose a framework for modeling/analyzing reservations in time-varying stochastic ridesourcing systems. We consider that the driver supply is distributed over a network of geographic regions and that book-ahead rides have reach time priority over non-reserved rides. First, we propose a state-dependent admission control policy that assigns drivers to passengers; this policy ensures that the reach time service requirement would be attained for book-ahead rides. Second, given the admission control policy and reservations information in each region, we predict the “target” number of drivers that is required (in the future) to probabilistically guarantee the reach time service requirement for stochastic non-reserved rides. Third, we propose a reactive dispatching/rebalancing mechanism that determines the adjustments to the driver supply that are needed to maintain the targets across regions. For a specific reach time quality of service, simulation results using data from Lyft rides in Manhattan exhibit how the number of idle drivers decreases with the fraction of book-ahead rides. We also observe that the non-stationary demand (ride request) rate varies significantly across time; this rapid variation further illustrates that time-dependent models are needed for operational analysis of ridesourcing systems. |
| Databáze: | OpenAIRE |
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