首页> 外文会议>International Conference on Computers in Railways; 2004; Dresden; DE >Human Factors Questionnaire measurement of engineer decision frequency
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Human Factors Questionnaire measurement of engineer decision frequency

机译:人为因素调查表工程师决策频率的测量

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The University of Virginia Center for Rail Safety-Critical Excellence (CRSCE) has developed a questionnaire for measuring railroad engineers' beliefs regarding the frequency of unusual action decisions based upon scenarios encountered during a daily work schedule. The questionnaire is designed to collect responses via a secure web-based interface. Scenarios describe railroad conditions such as work zones, temporary speed restricted zones, control point signal aspects, and emergency braking. Engineers are given the correct response according to rulebook regulations. Given these conditions, engineers are asked to rate the frequency of unusual action decisions of a hypothetical crew, based upon performance-shaping factors of fatigue, broad and specific experience, training, and attention. Engineers respond to categories of Never, Once in 50 years, Once in 20 years, Once in 5 years, Once in a year, Once in a month, or Regularly. Psychometric analyses include the estimation of probabilities of an action, given the scenario conditions and behavioural shaping factors. Item characteristics relating scenario-action rarity, and engineer response characteristics related to background experience, training, and work satisfaction are specified in the study design. Results will indicate the relative importance of work conditions and performance conditions towards predicting unusual action frequency so that railroad transportation safety and human decision-making is better understood.
机译:弗吉尼亚大学铁路安全关键卓越中心(CRSCE)已开发了一份调查表,用于根据日常工作时间表中遇到的情况,测量铁路工程师对异常操作决策频率的看法。该问卷旨在通过安全的基于Web的界面收集答复。方案描述了铁路条件,例如工作区,临时限速区,控制点信号方面和紧急制动。根据规则手册的规定,工程师将获得正确的响应。在这种情况下,要求工程师根据疲劳,广泛和特定经验,培训和关注的绩效塑造因素,对假设的机组做出异常行动决定的频率进行评估。工程师对“永不”,“ 50年一次”,“ 20年一次”,“ 5年一次”,“一年一次”,“一年一次”,“每月一次”或“定期”等类别进行响应。心理测量分析包括在给定情景条件和行为塑造因素的情况下对动作概率的估计。研究设计中指定了与场景动作稀有性相关的项目特征以及与背景经验,培训和工作满意度相关的工程师响应特征。结果将表明工作条件和性能条件对于预测异常动作频率的相对重要性,以便更好地理解铁路运输安全和人为决策。

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