User-driven cloud transportation system for smart driving

Intelligent transportation systems (ITS) have emerged as an efficient and effective way of alleviating the traffic congestion and improving the performance of transportation systems. Key challenges of ITS in recent years include the pervasive data collection, data security, privacy preserving, large volume data processing, and intelligent analytics. These challenges lead to a revolution in ITS development by leveraging the crowdsourcing scheme and cloud computing architecture. In this paper, we propose a user-driven Cloud Transportation system (CTS) which employs a scheme of user-driven crowdsourcing to collect user data for traffic model construction and congestion prediction including data collection, filtering, modeling, intelligent computation and publish. We describe in details the application scenario, system architecture, and core CTS services model. To verify the feasibility of our approach, we have developed a prototype system which elaborated the cloud architecture and other implementation details. This paper aims to inspire further research of user-driven CTS on intelligent data processing model for smarter utilization of transportation infrastructure.