Research On Influence Factors And Countermeasures Of Heavy Goods Vehicle Traffic Accident Severity

With the rapid development of China’s economy,the total amount of freight transport is also growing.Road freight transport is very important to integrated cargo transport system in China.With the advantage of its large volume,the heavy goods vehicle has become an important part of road freight transport,however,the proportion of heavy goods vehicles involved in traffic accidents is very high,especially that with serious casualty traffic accidents.These traffic accidents have brought great harm to people’s lives and property,so it is necessary to study the factors influencing the traffic accident severity of heavy goods vehicle and the corresponding countermeasures.Based on traffic accident data of heavy goods vehicles in Shenzhen,and with the application of various methods including descriptive statistical analysis,Grey Relational Analysis and Bayesian Network analysis,the characteristics of heavy goods vehicle traffic accidents and influencing factors of heavy goods vehicle traffic accidents severity had been explored in this paper.Firstly,the relevant researches on heavy goods vehicles and traffic accident severity had been reviewed.The basic concept of heavy goods vehicles,traffic accidents and the classification of the traffic accidents severity had been introduced.Based on the traffic accident data of heavy goods vehicles collected and organized,preliminary analysis of heavy goods vehicle traffic accidents had been examined from the aspects of driver,vehicle,road and environment,and the characteristics of heavy truck traffic accidents had been learned.Secondly,with the number of fatal accidents in traffic accident data as a reference sequence,the main factors strongly related to the heavy goods vehicle traffic accidents severity were screened out in this paper through Gray Relational Analysis.Then the data set and the test set based on the selected main factors had been built.Thirdly,a Bayesian Network model based on the data set had been bulit.The structure of Bayesian Network had been constructed via independent verification.The parameter estimation of Bayesian Network had been conducted by EM algorithm.Then the validity verification of the model had been carried out based on the test set.The Bayesian Network model for analysis of the heavy goods vehicle traffic accidents severity had been determined,and the reasoning analysis had been carried out based on this model.Finally,based on the reasoning analysis of Bayesian Network,both the hidden dangers of traffic accident and the problems in the supervision and management of heavy goods vehicles in Shenzhen had been analyzed in detail,and the countermeasures of improving supervision and management measures as well as road hardware conditions had been put forward,to improve the traffic safety level of heavy goods vehicles.The countermeasures of improving supervision and management measures include improving the relevant legal system for the management of heavy goods vehicle drivers,strengthening the daily joint law enforcement,increasing the intensity of safety inspection of heavy goods vehicles,strengthening the responsibility of transport enterprises,carrying out targeted traffic safety publicity,and making full use of the public supervision and service platform of road freight vehicles.The countermeasures of improving road hardware conditions include improving the basic safety facilities of the road,setting up the early warning facilities for pedestrians and non-motorized vehicles to break into the freeway,setting up special roads for non-motorized vehicles,and optimizing the design of road intersections.