mT-Share: A Mobility-Aware Dynamic Taxi Ridesharing System

Due to the wide availability of taxis in a city and the tremendous benefits of ridesharing, taxi ridesharing becomes promising and attractive in recent years. Existing taxi ridesharing schemes simply match ride requests and taxis based on partial trip information and omit the offline passengers, who will hail a taxi at the roadside without submitting the ride requests to the system. Thus, they are still not efficient and practical. In this article, we consider the mobility-aware taxi ridesharing problem and present
mT-Share
to address these limitations.
mT-Share
fully exploits the mobility information of taxis and ride requests to achieve efficient indexing of taxis/requests and better passenger–taxi matching, while still satisfying the constraints on passengers’ deadlines and taxis’ capacities. Specifically,
mT-Share
makes use of both geographical information and travel directions to index taxis and ride requests and supports the shortest path-based routing and probabilistic routing to serve both online and offline ride requests. In addition,
mT-Share
proposes a novel payment model to share the ridesharing benefits among the taxi driver and passengers. Extensive evaluations using a large real-world taxi data set demonstrate the efficiency and effectiveness of
mT-Share
, which can respond each ride request in milliseconds and be with moderate detour costs and passengers’ waiting time. Compared to state-of-the-art schemes,
mT-Share
can serve 42% and 62% more ride requests in peak and nonpeak hours, respectively. Furthermore,
mT-Share
can save 8.6% taxi fare for passengers and meanwhile increase 7.8% incomes for taxi drivers, when compared with the regular taxi services.