Optimizing Matching Time Interval and Matching Radius In On-Demand Matching of a Ride-Sourcing Market
Yang, H., Qin, X., Ke, J., & Ye, J. (2020). Optimizing matching time interval and matching radius in on-demand ride-sourcing markets. Transportation Research Part B: Methodological, 131, 84-105.
42 Pages Posted: 14 May 2019 Last revised: 30 Aug 2021
Date Written: April 15, 2019
With the availability of location information on drivers and passengers, ride-sourcing platforms are now able to provide more efficient online matching than the physical searching and meeting in traditional taxi market. The matching time interval (a time interval over which waiting passengers and idle drivers are accumulated and then peer-to-peer matching is executed) and matching radius (or maximum allowable pickup distance, within which matching or pairing between waiting passengers and idle drivers can be done) are two key control variables that the platform can employ to optimize the system performance in an online matching system. By appropriately extending matching time interval, the platform can accumulate more waiting (or unserved) passengers and idle drivers and thus match the two pools with shorter expected pickup distance. However, if the matching time interval is excessively long, some passengers may become impatient, and may even cancel their requests. Meanwhile, a short matching radius can reduce expected pickup distance but may decrease the matching rate as well. Therefore, it is important to optimize the matching time interval and matching radius to enhance system efficiency in terms of passenger waiting time, vehicle utilization and matching rate. This paper proposes a model to delineate the online matching process in a ride-sourcing market. The model is then used to examine the impact of the matching time interval and matching radius on system performance and to jointly optimize the two variables under different levels of supply and demand. Numerical experiments are conducted to demonstrate how the proposed modelling and optimization approaches can improve real-time matching processes of ride-sourcing platforms.
Keywords: ride-sourcing, online matching, matching time interval, matching radius
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