突发公共卫生事件下航空运行中的人与组织风险模型

Human and Organizational Factors in Aviation Operation Risk under Public Health Emergencies

目的为加强疫情背景下的航空安全管理,构建基于贝叶斯网络的人为因素分析和分类系统(HFACS-BN)的公共卫生事件下航空运行安全人为与组织因素贝叶斯网络的人为因素分析和分类系统(HOFs)风险概率评价模型。方法基于人为因素分析和分类系统(HFACS)识别和分类公共卫生事件下航空运行风险中的HOFs,并将其转化为贝叶斯网络(BN)框架,通过参数学习预测相关风险出现的概率,通过敏感性分析HOFs的敏感性程度。结果受公共卫生事件影响的飞行不安全行为中,技能差错的概率高达74.97%,是关键风险因素;航空组织在预案上缺乏对飞行员生理、心理特征的考量进而导致不安全行为,是最可能的致因机制。结论飞行员能力不足和感觉错误对飞行不安全行为敏感性较高。

Objective In order to strengthen aviation safety management in the context of epidemic situation,a probability assessment model of human and organizational factors(HOFs)of aviation operation safety under public health emergencies based on HFACS-BN was constructed.Methods Based on human factor analysis and classification system(HFACS),HOFs in aviation operation risks under public health emergencies were identified and classified,and transformed into a Bayesian network(BN)framework.The probability of related risks was predicted through parameter learning,and the sensitivity of HOFs was analyzed.Results Among the unsafe flight behaviors affected by public health emergencies,the probability of skill-based errors was as high as 74.97%,which was the key risk factor;The most likely cause mechanism is the lack of consideration of pilots'physiological and psychological characteristics in aviation organizations'contingency plans,which leads to unsafe behaviors.Conclusion The pilots'lack of ability and sensory errors are highly sensitive to unsafe flight behaviors.