CREAM追溯法在交通事故人因分析中的应用研究

Practical research into the cognitive reliability and error analysis of the human factors in traffic accidents

人因失效是道路交通事故发生的主要原因。认知可靠性和失误分析方法(CREAM)可以追溯事故发生的根原因,并对事故隐患进行预测。它强调情景环境对人的行为的重要影响,较符合驾驶员可靠性分析的需求。研究了CREAM中的追溯分析方法在道路交通人因失效事件根原因分析中的应用,建立了道路交通事故的人因失效模式,对人因失效基本原因的分类和后果-前因关系进行归纳、整理和补充,提出了适用于道路交通人因失效事件的"后果-前因"追溯表和具体的追溯分析步骤。进而对其定量计算进行了探索,并通过实例探讨了其应用,得到事故发生的根原因。

The present paper is aiming to analyze the root cause of human errors leading to disastrous human casualty and other kinds of traffic or transportation accidents by using the retrospective analysis method known as CREAM （cognitive reliability and error analysis method）. CREAM is also known as the representative second-generation human reliability analysis method to retrospect the deep-rooted cause of the traffic accidents and ways to predict their chance probability. The paper emphasizes the key influence of the context of the scenario on human behaviors and the drivers＇ performance because their driving behaviors are not isolated but influenced by the contextual situations they are involved in. In pursuing our research goal, we have analyzed the deep-rooted cause of human errors in the road traffic accidents with the retrospective analysis method in CREAM. First of all, a brief introduction to CREAM method, stressing the importance of intuitive understanding of the ineffective psychology and establishing human error identification model of road traffic accidents including four aspects, including slip, omission, violation and fault-commission. And, next, detailed recognized statistical data table of the accidents on the highway are given, which prove that human error is the key factor leading to the road traffic accidents. Moreover, the human errors are classified according to the relationship between the consequential and predictable factors, and then reorganized and complemented according to the actual facts. A data table of predictable causes can be shown. A simple consequential-antecedent retrospective table has been offered which is fit for the complex human error analysis and the process of the retrospective analysis has been prepared for practical application. We have also proposed items for further discussion of the quantitative and qualitative calculations so as to disclose the root causes leading to such disasters. In addition, we have also worked out a framework of the whole retrospective recollection for intuitive understanding. And, finally, the method has been trial-used in a retrospective analysis of a case road traffic accident, the vivid result demonstrating that the deep-root causes of the accident lie in the inefficient management, equipment failure, bad road conditions, the driving cognitive tendency, personality defects and the slackening attention. Thus, the conclusion made in this paper can provide useful guidance for human error analysis in road traffic faults-seeking and identification.