Research On Driver 's Risk Awareness

According to road traffic accident statistics both domestic and abroad, there are about more than 80 percent of traffic accidents which were caused by human factors are related to the errors made by the driver’s perception and judgment on the risk that present in the environment. Therefore, the issue on driver’s risk perception mechanism is essential to prevent traffic accidents with human factor point, so the study for the risk perception of the driver has very important theoretical and practical significance.This topic is based on driving simulation system platform KMRTDS and driving adaptability detection system, aiming at typical driving risk situations to start research on driver’s risk perception utility. The difference of driver’s risk perception utility types are presented and analyzed, and has also studied the relationship among driver’s risk perception utility, driving behavioral characteristics and driving adaptibility characteristics. Specific content as follows:First, combined the theory of risk perception and utility, proposed the concept of driver’s risk perception utility to describe the risk perception characteristics of the driver, and then constructed risk driving situations for experimental test, and determine the quantitative evaluation method of driver’s risk perception utility based on the degree of risk situation.Secondly, used driving simulation platform to have simulated driving experiment, driving adaptibility test and subjective risk evaluation on 31 driver. Quantitatively assessed the driver’s risk perception utility based on the experimental data, finally get the quantitative value of driver’s risk perception utility. The statistical analysis method from SPSS was used to make differences and clustering analysis for the quantitative value of driver’s risk perception utility. The differences analysis results showed that there are different degrees of difference for the driver’s risk perception utility due to the driver’s driving experience, driver’s age and driver’s gender; Cluster analysis results showed that different drivers with different risk perception characteristics in a typical risk driving situation, then categorized the driver into four types, namely conservative (cautious) type, intermediate type, radical (adventure) type and complex type.Finally, based on the driver’s classification results, used statistical analysis and wavelet analysis to analyze driving behavior characteristics from two aspects including the vehicle running status characteristics and the driver operation behavior characteristics. The results showed that:the conservative driver’s the value of risk perception utility is higher, the driving behavior is more stable and more secure; the aggressive driver’s the value of risk perception utility is lower and the driving behavior is less stable and less secure; when the intermediate driver’s the value of risk perception utility is at an immediate level their driving behavior stability and security are at an intermediate level; the complex driver in high-risk situations the value of risk perception utility and the driving behavior tend to be conservative and the drivers in low-risk situations tend to be aggressive. In addition, the results of driving adaptibility characteristics analysis showed that: The intermediate, complex driver’s driving adaptability is relatively better, and the aggressive, conservative driver’s driving adaptibility relatively poorer.In this study, researching driver’s risk perception utility was the key point, and proposed a driver classification method based on risk perception utility, and based on this classification method to study the relationship among driver’s risk perception utility, driving behavioral characteristics and characteristics of driving adaptability. The results of the research were not only helpful to test driver’s driving dynamics adaptiblity, but also promoted the exploration and study of driver’s risk perception process.