Design of Freeway Automatic Incident Detection System and Algorithm

As high as 60% to 70% of the traffic delay experienced by motorists in developed countrics is attributed to traffic incident. A substantial reduction in this delay can be achieved by early detection of the incidents that cause it and prompt response to divert the traffic in the upstream flow. Since the late 60s of 21th, Automatic Incident Detection (AID) systems have been developed and implemented to help traffic management authorities. However, high false alarm rates and low poor performance of the adopted AID system have caused some authorities to abandon them. To enhance the reliability, transferability and economization of AID system, a framework for freeway AID system with three grade alarm policy is put forword, and an AID algorithm based on the Artificial Neural Networks (ANN) technology that only need single detector is designed. It was proved by simulated data that the model built on one segment can be utilized to other segments, and all three measurements (DR, FAR and MTTD) are superior to the objective algorithm. Furthermore, the total cost of freeway incident management system can be reduced due to only single detector is needed for one detector station.