基于神经网络的交通事件检测算法

Artificial Neural Network(ANN) Algorithm for Traffic Incidents Detection

回顾了几种传统的交通事件检测算法 ,提出从多层前向人工神经网络角度建立模型 ,并运用 BP算法予以实现。在将 BP算法与传统算法进行比较之后 ,发现 BP算法具有检测率高、误报率低、检测时间短的优点 ,同时也存在不足之处 ,指出了今后进一步研究的方向。

Several traditional algorithms used in traffic incident detection are reviewed. A detection model based on artificial neural network is proposed and implemented with a BP algorithm. By comparing the ANN model with California algorithm, It is found that the performance of the ANN algorithm has higher detection rate, lower false alarm rate, shorter mean detection time and some disadvantages. The further research directions are given.