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Road traffic big data collision analysis processing framework

With the advancement of sensor technologies, big data processing becomes a new paradigm for large scale information processing. Big data comes from different sources, such as from traffic information, social sites, mobile phone GPS signals and so on. In this paper, we propose a new architecture for distributed processing that enables big data processing on the road traffic data and its related information analysis. We applied Hadoop and HBase that can store and analyze real-time collision data in a distributed processing framework. This framework is designed as flexible and scalable framework using distributed CEP that process massive real-time traffic data and ESB that integrates other services. We tested the proposed framework on road traffic data on a 45-mile section of I-880N freeway CA, USA. By integrating freeway traffic big data and collision data over a ten-year period (1TB Size), we obtained the collision probability.