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A comprehensive human factors analysis of off-duty motor vehicle crashes in the United States military.

机译:美国军队下班机动车碰撞的综合人为因素分析。

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摘要

Researchers have always had great interest in traffic safety and the phenomenon of motor vehicle crashes (MVCs). Though scores of service members are severely injured or killed in off-duty MVCs each year, few studies have addressed the MVC phenomenon within the military population and none have conducted a comprehensive evaluation of the causal factors associated with MVCs involving military personnel.;The main purpose of this dissertation was to gain a greater understanding of the causal factors associated with serious and fatal off-duty personal MVCs for military service members with the ultimate goal of preventing future losses. The HFACS-MVC framework was developed based on the established human error framework HFACS and used to classify causal factors from archival narratives from Class A and B off-duty MVCs in the USAF, USN, and USMC. This study identified the human factors trends associated with off-duty military MVCs and compared main trends for four variables of interest, specifically for military branch, vehicle type, paygrade, and age group.;The main human factor trends associated with off-duty MVCs were skill based technique errors related to negotiating curves/turns and regaining road positions and procedural violations related to speeding and drunk driving. Significant differences were found between human factors trends associated with MVCs for both vehicle type and military branch. For vehicle type, the human factors trends for 4W MVCs were significantly different from those for 2W MVCs, especially at the preconditions level. However, for military branch, the human factors trends suggest differences in the investigation and reporting processes for the three branches.
机译:研究人员一直对交通安全和机动车碰撞现象(MVC)感兴趣。尽管每年都有数十名服务人员在下班的MVC中受重伤或丧生,但很少有研究针对军人内部的MVC现象,也没有一项针对涉及军事人员的MVC的因果因素进行过全面评估。本文的目的是为了更好地理解与严重和致命的免役个人MVC相关的因果关系,最终目的是防止未来损失。 HFACS-MVC框架是基于已建立的人为错误框架HFACS开发的,用于对来自美国空军,USN和USMC的A级和B级下班MVC档案叙述的因果因素进行分类。这项研究确定了与下班军事MVC相关的人为因素趋势,并比较了四个感兴趣变量的主要趋势,特别是针对军事部门,车辆类型,薪资和年龄组。;与下班MVC相关的主要人为因素趋势是基于技巧的技术错误,这些技术错误与弯道/转弯和重新获得道路位置有关,并且与超速驾驶和酒后驾驶有关。在车辆类型和军事部门的与MVC相关的人为因素趋势之间发现了显着差异。对于车辆类型,4W MVC的人为因素趋势与2W MVC的人为趋势显着不同,尤其是在前提条件级别上。但是,对于军事部门,人为因素趋势表明这三个部门的调查和报告过程有所不同。

著录项

  • 作者

    Iden, Rebecca Michelle.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Psychology Behavioral.;Transportation.;Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 281 p.
  • 总页数 281
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:42:29

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