胡杰,许力,孟武强,刘慧,孟濬.基于相空间重构的驾驶风格定量评估[J].仪器仪表学报,2017,38(3):635-642
基于相空间重构的驾驶风格定量评估
Quantitative evaluation of driving style based on phase space reconstruction
  
DOI:
中文关键词:  驾驶风格  驾驶行为  相空间重构  关联维数
英文关键词:driving style  driving behavior  phase space reconstruction  correlation dimension
基金项目:福特汽车公司大学研究计划(URP 2014 8014R)、浙江省科技计划项目(2017C31079)资助基于相空间重构的驾驶风格定量评估
作者单位
胡杰 浙江大学电气工程学院杭州310027 
许力 浙江大学电气工程学院杭州310027 
孟武强 福特汽车工程研究(南京)有限公司南京211100 
刘慧 福特汽车工程研究(南京)有限公司南京211100 
孟濬 浙江大学电气工程学院杭州310027 
AuthorInstitution
Hu Jie College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China 
Xu Li College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China 
Meng Wuqiang Ford Motor Research and Engineering (Nanjing) Co., Ltd., Nanjing 211100, China 
Liu Hui Ford Motor Research and Engineering (Nanjing) Co., Ltd., Nanjing 211100, China 
Meng Jun College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China 
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中文摘要:
      驾驶风格评价是智能交通领域的重要研究课题,一般采用频域或时域的分析方法对其进行定性的分类和识别,缺乏客观定量的评价体系。提出一种基于相空间重构的驾驶风格定量分析方法。首先,采用汽车测试数据和局部性神经网络建立个性化的驾驶员模型;然后,将个性化驾驶员模型应用于标准驾驶周期测试工况的速度跟随试验,以实现驾驶行为的标准化;最后,对标准化驾驶行为进行相空间重构,提出一种基于关联维数的驾驶风格指数,用于定量评估驾驶的激进程度,并应用于驾驶员风格的识别,仿真结果验证了所提方法的有效性。
英文摘要:
      Driving style evaluation is an important research topic in the field of intelligent transportation, which is usually recognized and classified qualitatively using time or frequency domain analysis methods and lacksobjective, quantitative evaluation system. A quantitative analysis method for driving style of the driver based on phase space reconstruction is proposed. Firstly, the vehicle test data and local neural network are adopted to establish a personalized driver model. Secondly, the personalized driver model is applied to the speed tracking test in normalizeddriving cycle test to achieve the normalization of driving behavior. Finally, the phase space reconstruction of the normalized driving behavior is conducted, a driving style index is proposed based on the correlation dimensionand used for quantitatively evaluating the aggressiveness of the driving behavior. The driving style index is further applied to the recognition of driving styles. Simulation results verify the effectiveness of the proposed method.
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