吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (12): 3342-3350.doi: 10.13229/j.cnki.jdxbgxb.20220173
• 车辆工程·机械工程 • 上一篇
袁伟1(),袁小慧1,2,高岩3,李坤宸1,赵登峰4,刘朝辉4
Wei YUAN1(),Xiao-hui YUAN1,2,Yan GAO3,Kun-chen LI1,Deng-feng ZHAO4,Zhao-hui LIU4
摘要:
针对驾驶人误踩踏板引发电动公交失控问题,开展了自然驾驶试验和误踩踏板的模拟驾驶试验,采用One-Class SVM和iForest方法建立了踏板误操作辨识方法。试验结果表明:车速、电机转矩、加速踏板开度和制动踏板开度可作为反映踏板误操作行为的特征参数;One-Class SVM和iForest辨识方法识别准确率分别为94.9%和99.5%,但iForest辨识方法在踏板误操作行为的识别精确率方面具有突出优势。利用iForest辨识方法对电动公交运行数据进行辨识,可为降低误踩踏板相关事故发生提供理论支持。
中图分类号:
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