Abstract
With rapid development of sensor technologies and wireless network infrastructure, research and development of traffic related applications, such as real time traffic map and on-demand travel route recommendation have attracted much more attentions than ever before. Both archived and real-time data involved in these applications could potentially be very big, depending on the number of deployed sensors. Emerging Cloud infrastructure can elastically handle such big data and conveniently providing nearly unlimited computing and storage resources to hosted applications, to carry out analysis not only for long-term planning and decision making, but also analytics for near real-time decision support. In this paper, we propose Smart Traffic Cloud, a software infrastructure to enable traffic data acquisition, and manage, analyze and present the results in a flexible, scalable and secure manner using a Cloud platform. The proposed infrastructure handles distributed and parallel data management and analysis using ontology database and the popular Map-Reduce framework. We have proto-typed the infrastructure in a commercial Cloud platform and we developed a real-time traffic condition map using data collected from commuters' mobile phones.