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Distributed situation assessment for traffic emergent events

The concept of the Internet of Things provides a new model to access the information of the objective world. A new approach based on the Internet of Things for traffic emergent events is proposed. The network architecture entails a hierarchy of capability, information and control, where nodes in the network expected to possess resources for networking and computing and presume autonomy through multi-functional modules for sensory processing and situation assessment. For the data fusion of multi-sensor device, the paper puts forward three different methods of date fusion according to different integrality levels of raw information. Finally, Bayesian network method is used to get situational assessment of the fused data. Comprehensive experiments on urban traffic emergent events of Dalian and comparisons with several other methods show that the Bayesian network combined with the Internet of Things is a very promising and effective approach for traffic emergent events' situation assessment modeling and forecasting, both for complete data and incomplete data.