Real-time adaptive on-line traffic incident detection

A new approach to traffic incident detection is proposed in this paper. The method consists of two stages. In the first stage, a real-time adaptive on-line procedure is used to extract the significant components of traffic states, namely, average velocity and density of moving vehicles. In order to effectively and efficiently account for the time-varying and random nature of traffic incidents, it is necessary to have a real-time on-line adaptive algorithm. In the second stage, we apply a new neural network called fuzzy CMAC to identify traffic incidents. Simulation results show that the performance is very good.