WEtransport: A Context-based Ride Sharing Platform

摘要

In densely populated urban areas high amounts of traffic pose a major problem, which affects the environment, economy, and our lives. From a user's perspective, the main issues include delays due to traffic jams, lack of parking space and high costs due to increasing fuel prices (e.g., if commuting long distances). Collective transportation (CT), e.g., public transport systems, provides a partly solution to these issues. 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 distances. A solution to these issues is ride sharing, an evolving form of CT making alternative transportation more affordable. In this paper we present a modular, context-aware ride sharing platform. We aim at enhancing convenience, reliability, 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.