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飞行员天气遭遇的分类与预测:判别函数分析

Classification and prediction of pilot weather encounters: A discriminant function analysis.

作者信息

O'Hare David, Hunter David R, Martinussen Monica, Wiggins Mark

机构信息

University of Otago, Dunedin, Otago, New Zealand.

出版信息

Aviat Space Environ Med. 2011 May;82(5):543-9. doi: 10.3357/asem.2739.2011.

DOI:10.3357/asem.2739.2011
PMID:21614869
Abstract

INTRODUCTION

Flight into adverse weather continues to be a significant hazard for General Aviation (GA) pilots. Weather-related crashes have a significantly higher fatality rate than other GA crashes. Previous research has identified lack of situational awareness, risk perception, and risk tolerance as possible explanations for why pilots would continue into adverse weather. However, very little is known about the nature of these encounters or the differences between pilots who avoid adverse weather and those who do not.

METHODS

Visitors to a web site described an experience with adverse weather and completed a range of measures of personal characteristics.

RESULTS

The resulting data from 364 pilots were carefully screened and subject to a discriminant function analysis. Two significant functions were found. The first, accounting for 69% of the variance, reflected measures of risk awareness and pilot judgment while the second differentiated pilots in terms of their experience levels. The variables measured in this study enabled us to correctly discriminate between the three groups of pilots considerably better (53% correct classifications) than would have been possible by chance (33% correct classifications).

CONCLUSIONS

The implications of these findings for targeting safety interventions are discussed.

摘要

引言

飞入恶劣天气对通用航空(GA)飞行员来说仍然是一个重大危险。与天气相关的坠机事故的死亡率明显高于其他通用航空坠机事故。先前的研究已经确定,缺乏态势感知、风险认知和风险承受能力可能是飞行员继续飞入恶劣天气的原因。然而,对于这些遭遇的性质以及避免恶劣天气的飞行员和不避免恶劣天气的飞行员之间的差异,我们知之甚少。

方法

网站访问者描述了一次恶劣天气经历,并完成了一系列个人特征测量。

结果

对364名飞行员的所得数据进行了仔细筛选,并进行了判别函数分析。发现了两个显著函数。第一个函数解释了69%的方差,反映了风险意识和飞行员判断力的测量结果,而第二个函数则根据飞行员的经验水平对他们进行了区分。本研究中测量的变量使我们能够比随机分类(33%的正确分类)更好地(53%的正确分类)正确区分三组飞行员。

结论

讨论了这些发现对确定安全干预目标的意义。

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