Highway Tunnel Incident Detection And The Best Speed Algorithm Research

In order to reduce tunnel traffic jam and vehicle delay, ensure vehicles securely tunnel through, offer scientific basis for managers, considering the tunnel traffic environment characteristics and the basic theories of traffic flow; this paper studies the following questions.The concept of highway tunnel incident and its own characteristics are expounded, and the impact of highway tunnel incidents to the traffic flow is analyzed. Based on the present research on highway tunnel incident detection algorithm abroad and in our country, this paper adopts artificial neural network and sets up the incident detection model of dynamic probability neural network (DPNN) according to the artificial neural network, a formidable non-model pattern sorter. Input index is not the individual traffic flow parameter, but the combination of traffic parameters, so the traffic incident information in traffic data can be used completely; and performs data filtering process, greatly enhances the algorithm performance.As we know the speed of vehicle is an important reason that initiates the tunnel traffic accident, in order to determine a best driving speed, this paper has proposed an optimized speed algorithm, which based on a two layer fuzzy logic. This algorithm avoids the difficulty of establishing the model of traffic flow compared to the traditional algorithm. Moreover considering the actual situation; this algorithm has made full use of the information closely related to speed , such as road condition,environment. The optimum speed determined by the traffic condition, providing a practical reliable basis for invariable speed control.