Research On The Causative Factors Of Road Traffic Accidents

Human factors play an important role in the cause of accidents.A large number of accident investigation results show that human factors are the main cause of accidents.Creat accident model is the foundation of the accident investigation and analysis.The different accident investigation methods and results are different with the different accident models used.In this paper,based on HFACS(human factors analysis and classification system),the classification framework of traffic accident causative factors is established,the relationship between each level and the first level causative factors in the whole system is measured,and the accident chains and accident factors with the highest probability are analyzed.Then the input and output probabilities between adjacent levels in the whole system are further calculated.Finally,considering the limitations of HFACS,a new model is proposed on the basis of HFACS and its rationality is tested.The research conclusions are as follows:(1)The system of causative factors of road traffic accidents has the characteristics of complexity and hierarchical structure.However,HFACS is only a qualitative analysis model and cannot determine the major contributing factor chains and contributing factors.Therefore,we construct a hybrid approach that integrates HFACS,Bayesian networks and shortest path problems.The results show that the longest causal chain“regulatory authorities--organizational climate--supervisory violations--substandard conditions of operator--overload/overcrowding” contains almost all important human factors.The influence of each level in the HFACS framework of the first level is gradually decreasing,that is,from “preconditions of unsafe acts”,to“unsafe supervision ”,to “organizational influences”,and finally to “outside factors”.This hybrid method combines qualitative research with quantitative research,which obviously has a great advantage over qualitative research or quantitative research alone.(2)To HFACS framework in a hierarchy as input,the next level as the output,quantitatively investigated the influence of the relationship between the adjacent level,finds out some factors affecting the main cause of road traffic accidents,such as“substandard practice of operators”,“inadequate supervision”,“resource/ acquisition management”,“organizational climate” and “regulatory authorities”.The results show that HFACS and NNs(neural network)can be integrated completely,which provides a new perspective and an idea for better understanding of road traffic accidents.(3)The new system-based approach,which combines HFACS and CFIM,highlights the interaction between causal categories at all levels and is an appropriate approach for analyzing road traffic accidents.All potential categories,including “outside factors”,“organizational influences”,“unsafe supervision”,and “preconditions of unsafe acts”,are significantly correlated with “unsafe acts”,more importantly,“outside factors”,“organizational influences ”,“unsafe supervision” and “preconditions of unsafe acts”can interact with each other,but these interactions have not been quantitatively studied in previous studies.