Optimizing Taxi-Pooling Operations to Enhance Efficiency and Revenue: A Queuing Model Approach

Chaojun Wang, Jingwei Wang, Yi Zhang, Jairus Odawa Malenje and Yin Han ()
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Chaojun Wang: Smart Urban Mobility Institute, University of Shanghai for Science and Technology, Shanghai 200090, China
Jingwei Wang: Department of Traffic Engineering, Huaiyin Institute of Technology, Huaian 223003, China
Yi Zhang: Shanghai Municipal Institute of Urban and Rural Construction and Transportation Development, Shanghai 200032, China
Jairus Odawa Malenje: School of Computing and Informatics, Masinde Muliro University of Science and Technology, Kakamega 190-50100, Kenya
Yin Han: Smart Urban Mobility Institute, University of Shanghai for Science and Technology, Shanghai 200090, China

Mathematics, 2024, vol. 12, issue 20, 1-22

Abstract: This study investigates the optimization of taxi-pooling operations using the M / M /1/ m queuing model, aiming to enhance efficiency and revenue for taxi service platforms. Traditional taxi operations face challenges during peak periods, including inefficiency and increased operational costs. Taxi-pooling, by accommodating multiple passengers with similar travel demands, offers a solution that reduces travel costs, operational expenses, and urban congestion. The study develops an optimization model to balance operational costs and passenger waiting times, identifying the utilization rate of taxis as a critical factor in platform revenue. By modeling the taxi-pooling service as a queuing system, we derive mathematical expressions for passenger waiting times and platform revenue under varying conditions. Our findings highlight the importance of optimal vehicle investment strategies and pricing decisions to maximize revenue. The study provides theoretical support for improving taxi-pooling platforms’ efficiency and competitiveness, contributing to better urban transportation solutions.

Keywords: taxi-pooling optimization; M / M /1/ m queuing model; revenue maximization; passenger waiting time (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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