Driving Style-based Sensitivity Analysis of Driving Risk Field in Mountain Highway Sections Passing Through Villages and Towns
In response to the high frequency of traffic accidents on mountainous roads passing through villages and towns,this paper proposes a driving risk identification method considering driving style and reveals the influence of driving style in risk assessment through sensitivity analysis.The method is verified with a typical mountainous road passing through villages and towns in Yunnan Province as an example.The vehicle trajectory data is collected through drones and a trajectory database is established for the analysis.Based on the theory of driving risk field and through correlation analysis of accident data,the impact of driving environment on vehicle driving in the village and town section is characterized.Furthermore,driving style factors are introduced to establish a driving risk field that considers driving style,achieving comprehensive consideration of multiple factors and quantification of driving risk.Based on the Sobol global sensitivity analysis method,the global sensitivity of key parameters of the model before and after considering driving style is analyzed,and the visualization of regional risks is realized.The results indicate that when selecting the mean velocity,mean acceleration,and variance of impact for driving style classification,the clustering effect is best when the K value is 4.The Sobol method effectively evaluates parameter sensitivity.When considering the driver behavior field,the overall sensitivity distribution is more uniform,and the model considers a wider range of factors.Among them,the standard deviation of speed and impact are the most significant parameters,and the overall sensitivity is respectively 0.41 and 0.34.The visualization of the risks generated by the joint action of multiple vehicles shows that the potential field range varies with the shape of the road,and the risk value is most significant at the intersection through villages and towns,with an overall speed reduction ratio of 17.39%.This will further enhance the role of risk field theory in the field of micro traffic risk assessment.
traffic engineeringrisk field modelsensitivity analysisroad through the village and towndriving stylemountain roads
万方数据
维普
