WEtransport: A Context-based Ride Sharing Platform

In densely populated urban areas high amounts of traffic pose a major problem, which affects the environment, econ-omy, and our lives. From a user’s perspective, the main is-sues include delays due to traffic jams, lack of parking space and high costs due to increasing fuel prices (e.g., if commut-ing long distances). Collective transportation (CT), e.g., pub-lic transport systems, provides a partly solution to these is-sues. Yet, CT does not support door-to-door transportation hence reducing convenience; it might be limited in off-peak hours, and it is still a cost factor when travelling long dis-tances. A solution to these issues is ride sharing, an evolving form of CT making alternative transportation more afford-able. In this paper we present a modular, context-aware ride sharing platform. We aim at enhancing convenience, reliabil-ity, and affordability of different forms of ride sharing by means of context data. Additionally our approach supports an easy server- and client-side expansion due to the modular platform structure. Author Keywords ride sharing, ticket sharing, mobile phone, collective transportation, car poolin