| With the continuous enhancement of China’s comprehensive national strength and the continuous improvement of residents’ living standards,the number of motor vehicles in China is also increasing year by year.Motor vehicles not only bring people convenient and fast travel experience,but also bring unpredictable risks.Traffic safety has also become a hot research field for scholars at home and abroad.Accident cause analysis is an important research method in the field of traffic safety,but the analysis of the state of people after the accident is relatively lacking.Therefore,the research on the survival time characteristics of drivers after traffic accidents is an important research topic in the field of traffic safety,which has great significance for reducing the death rate of traffic accidents and improving road traffic safety Great effect.In order to explore the impact of various factors in traffic accidents on the survival time of drivers,this paper uses the survival analysis method to conduct modeling analysis.Based on the Fars data in 2019 provided by the official website of NHTSA,the independent variables and dependent variables of the survival analysis model are determined through literature research.The independent variables include gender,whether drinking,age,age Based on the correlation analysis,the complex relationship between the six variables is clarified.Through the single factor and multi factor analysis of the variables,the influence of the driver’s survival time characteristics after the traffic accident is obtained.The main research contents are as follows:(1)The survival analysis model was established based on Kaplan Meier method,and the variables were analyzed by univariate analysis.The results show that sex,drinking or not,age,light conditions,seat belt usage and weather conditions have significant effects on the survival time of drivers in traffic accidents.Research shows that the survival time of male drivers is shorter than that of female drivers,and the risk of death at the same time is higher than that of female drivers;drinking alcohol can shorten the survival time of drivers and increase their risk of death;the risk of death of elderly drivers is the highest among all age groups.(2)Pearson correlation test was used to analyze the correlation among the six selected covariates.Through the analysis of Pearson correlation coefficient graph,it is found that there is no strong correlation between the six covariates selected in this paper.We can carry out multi factor relationship for these covariates,and describe the complex relationship between variables,classification and data distribution by means of cross contingency table and mosaic graph,which lays the foundation for multi factor analysis.(3)A Cox proportional hazards model was established to analyze the effects of six covariates on the results.The results showed that the six covariates had significant effects on the results.The results show that the death risk rate of drinking drivers is about 1.677 times that of non drinking drivers;the risk rate of misuse of seat belts is 1.696 times that of correct use of seat belts;the death risk rate of elderly drivers is about 1.374 times that of minor drivers.Finally,AIC and BIC are used to explore the optimal cut-off time of "driver survival time",which verifies the rationality of this study,enhances the practical significance of this paper,and paves the way for the further research of this topic.Through the research of this paper,it can provide decision-making suggestions for the traffic management department and Emergency Rescue Department,and also provide new ideas for the research in the field of traffic safety,which has certain theoretical innovation and practical significance. |
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