Incentivized user-based relocation strategies for moderating supply–demand dynamics in one-way car-sharing services

Abstract

One-way car-sharing services have drawn much attention in recent years in transportation research and practice. The flexible operating scheme stimulates patronage but causes unbalanced distributions of the shared cars and consequently low utilization of the services. In light of the empirical evidence that users are willing to cooperate with the operators for relocations, this paper formulates the supply–demand dynamics of shared cars under four user-based relocation strategies, including a naive one without incentive and three alternatives with incentives. We formulate the triggering conditions and travel disutilities responding to the incentive-based strategies based on the concept of load-space–time paths. To systematically assess the effects of the strategies, we propose an incentive-based boundedly rational dynamic user equilibrium (IBR-DUE) model in a multimodal transportation system. A cluster-based column generation algorithm is developed to solve the IBR-DUE model without path enumeration in a space–time supernetwork. Numerical examples demonstrate that the alternative drop-off incentive outperforms other strategies and can improve the utilization and service rates about 2 times on average.