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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(6): 236-249
WANG Ke, LU Jian, JIANG Yu-ming. Abnormal road driving behavior spectrum establishment and characteristic value calculation method based on vehicle driving trajectory[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 236-249. doi: 10.19818/j.cnki.1671-1637.2020.06.021
Citation: WANG Ke, LU Jian, JIANG Yu-ming. Abnormal road driving behavior spectrum establishment and characteristic value calculation method based on vehicle driving trajectory[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 236-249. doi: 10.19818/j.cnki.1671-1637.2020.06.021
shu

Abnormal road driving behavior spectrum establishment and characteristic value calculation method based on vehicle driving trajectory

doi: 10.19818/j.cnki.1671-1637.2020.06.021

  • College of Transportation Engineering, Tongji University, Shanghai 201804, China

Funds:

National Key Research and Development Program of China 2017YFC0803902

National Natural Science Foundation of China 71871165

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    Abstract
  • To quantitatively describe the dynamic change process of driving behavior and the degree of abnormal driving under different road driving scenarios, the establishment and analysis methods of abnormal driving behavior spectrum were studied. The driving behavior spectrum based on the key parameters of vehicle driving trajectory was established. The measurement of risk method was applied to quantify four types of abnormal driving behaviors, including abnormal car-following, serpentine driving, speed instability, and abnormal lane-changing. An abnormal driving behavior spectrum was established based on the driving behavior spectrum. Traffic flow conditions were divided based on the traffic volume-density relationship and the differences among the statistical parameters of driving behavior. Under different traffic flow conditions, the thresholds of the characteristic parameters of abnormal driving behaviors were determined by using the interquartile range method. The abnormal driving behavior scores of each driver were calculated based on the characteristic parameter thresholds. The weights of abnormal driving behaviors were determined by using the CRITIC weighting method and the characteristic values of the abnormal driving behavior spectrum for each driver were calculated. To verify the effectiveness of the method, vehicle driving trajectory data were collected by an unmanned aerial vehicle traffic video in Shanghai and the characteristics of car abnormal driving behavior were analyzed. The characteristic values of the abnormal driving behavior spectrum were verified by the expert scoring method. Analysis result shows that the traffic flow condition clustering method based on driving behavior parameters divides the traffic flow condition of data into three categories: free flow, saturated flow, and congested flow. The clustering method is more suitable for driving behavior analysis than the traffic flow condition division method based on the fundamental diagram. The characteristic parameter distributions of abnormal car-following, serpentine driving, and speed instability under different traffic flow conditions are significantly different. The occurrence of extreme values of abnormal car-following, serpentine driving, and speed instability under congested flow conditions is more frequent, while the abnormal lane-changing characteristic parameter has a similar distribution under each traffic flow condition. The thresholds of serpentine driving, speed instability, and abnormal lane-changing increase with the increase of traffic flow density. The weights of abnormal car-following, serpentine driving, speed instability, and abnormal lane-changing calculated by the CRITIC weighting method are 0.19, 0.33, 0.37, and 0.11, respectively. The distribution ranges of the abnormal driving behavior spectrum characteristic values under free flow, saturated flow, and congested flow are similar, all between 0 and 0.4. The expert's abnormal driving behavior evaluation is consistent with the abnormal driving behavior spectrum characteristic values. The establishment of an abnormal driving behavior spectrum and the calculation method of characteristic values can automatically identify abnormal drivers by using the vehicle driving trajectory data. The method is objective, adaptable, and reliable, and can detect abnormal drivers in time, providing drivers with safety tips and technical support for traffic safety early warning to traffic management departments.

     

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