EURO 2025 Leeds
Abstract Submission

1957. A Maximum Flow-Based Matching Model for Car-sharing Services: Integrating Pricing, Subsidies, and User Choice Behavior

Invited abstract in session WA-30: Shared Mobility Optimization I, stream Shared Mobility Optimization.

Wednesday, 8:30-10:00
Room: Maurice Keyworth 1.05

Authors (first author is the speaker)

1. Xin Wang
Institute for Transport Studies, University of Leeds
2. David Watling
Institute for Transport Studies, University of Leeds

Abstract

In car-sharing services, the efficiency of matching between renters and vehicle owners is a critical determinant of overall system performance and service quality. Rental owners’ decision-making processes are significantly influenced by pricing strategies and subsidies, which, in turn, affect the balance between supply and demand. Conversely, renters’ choices, when selecting among multiple available rental options, are shaped not only by price but also by factors such as proximity. Consequently, the development of an effective matching mechanism is essential for optimizing system efficiency. This study introduces a maximum flow-based matching model to optimize the allocation between renters and rental owners while incorporating mathematical modeling to analyze their decision-making behaviors. Specifically, a pricing and subsidy decision model is first formulated to examine how varying pricing and subsidy strategies influence the supply side. Subsequently, a nested logit model is constructed to characterize renters’ choice behaviors, accounting for the impact of both price and distance on rental decisions. For matching optimization, we employ the maximum flow algorithm to determine the optimal allocation of rental resources, aiming to maximize overall system utilization. Furthermore, we investigate the effects of different pricing and subsidy strategies on flow distribution and explore optimization schemes designed to enhance system efficiency and user satisfaction.

Keywords

Status: accepted

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