Applying event stream processing on traffic problem detection

Abstract

Sensor-based traffic management systems have to cope with a high volume of continuously generated events. Conventional software architectures do not explicitly target the efficient processing of continuous event streams. Recently, Event-Driven Architectures (EDA) have been proposed as a new paradigm for event-based applications. In this paper we propose a reference architecture for event-driven traffic management systems, which enables the analysis and processing of complex event streams in real-time. In particular we are going to outline the different stages of traffic event processing and present an approach based on event patterns to diagnose traffic problems. The usefulness of our approach has been proven in a real world traffic management scenario. © 2009 Springer Berlin Heidelberg.