Limited Information-Sharing Strategy for Taxi–Customer Searching Problem in Nonbooking Taxi Service

Abstract

One of the issues in current taxi service is the imbalance between supply and demand. In response to this issue, an automatic taxi-dispatching approach in which customers can book taxis through phones or mobile devices is widely used in many large cities worldwide. However, this approach is not satisfactory: most customers still prefer nonbooking taxi service (NBTS), taking the taxi by either waiting at a taxi stand or hailing one on the street. One important reason for this phenomenon is that customers take a lower risk in NBTS: they are free from complicated booking procedures and have no commitment to any as-yet-arrived taxis. To facilitate the taxi–customer matching process in NBTS, a novel control strategy is proposed—namely, the limited information-sharing strategy (LISS) for the taxi–customer searching problem in NBTS, in which both the taxi and the customer are equipped with mobile devices that can communicate with each other within limited searching ranges. The proposed LISS is based on the game theoretical formulation in which a learning algorithm to find the pure Nash equilibrium is developed. A microscopic traffic simulation model for evaluation of the LISS is developed. The simulation results show that the proposed LISS is an effective control strategy when taxi supply is low and will not increase the risk of the taxi driver in losing the total occupied time.