汽车驾驶员主动安全性因素的辨识与分析

Identification and Analysis of Driver's Active Safety Factors

将驾驶员主动安全性的辨识分成熟练、疲劳程度两个独立的部分进行评价 ,并在实验的基础上 ,通过抽取与驾驶员熟练、疲劳程度相关联的特征参数的方法 ,按照实验统计结果划分成模糊子集 .通过 3个分层的模糊神经网络分别对驾驶员的熟练、疲劳程度和综合的主动安全性进行辨识和分析 ,对各个子网络采用改进的 BP算法进行学习和训练 ,达到许用误差后 。

The identification and evaluation of driver's active safety factors are the keystone and difficulty of the evaluation of whole synthesized Man Vehicle Road system. The identification of driver's active safety was divided into the two independent parts: the evaluation of driver's skill and fatigue. Characteristic parameters of the driver's proficiency and fatigue were extracted based on the experiments, and they were divided into fuzzy subsets according to the statistic results. Therefore, the driver's degrees of proficiency, fatigue and active safety can be identified and analyzed. When the networks were trained with the improved BP algorithm and the accepted errors were reached, the driver's active safety factors can be identified scientifically and quantitatively.