A Mobile, Dynamic, and Privacy-Preserving Matching System for Car and Taxi Pools

Recently, rates of vehicle ownership have risen globally, exacerbating problems including air pollution, lack of parking, and traffic congestion. While many solutions to these problems have been proposed, carpooling remains one of the most effective approaches. Recently, several carpooling platforms have been built on cloud computing systems, with originators posting online list of departure/arrival points and schedules from which participants can search for rides that match their needs. However, it can be difficult to make matches quickly and the systems are subject to privacy concerns in that they may disclose private information such as names, registration data, and departure/arrival schedules. This paper proposes a dynamic matching method for car/taxi pools for use in mobile devices via ad hoc Wi-Fi networks. The proposed method also preserves user privacy including names and departure/arrival schedules. Moreover, the system does not require the user to register any personal data, so such data cannot be leaked. The system was implemented on the Android mobile platform, allowing users to immediately and securely access the system via their smart phones.