Recently the rapid development of Internet of Thing (IoT) brings new opportunity to Intelligent Transportation System (ITS). The key problem is how to process the huge events generated by IoT to support ITS. In this paper a proactive complex event processing method is proposed for congestion control in ITS. Based on complex event processing, this method predicts the traffic flow using a multi-layered Adaptive Dynamic Bayesian Network. When congestion is predicted, actions are chosen and executed based on concurrent-actions Markov Decision Processes (MDP) to avoid the future traffic congestion. The simulation experiments show that this method can reduce the traffic congestion obviously for typical transportation system.
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Yongheng Wang (2013) studied this question.
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