This descriptive–analytic study identified the factors affecting the degree of fatigue and sleepiness of heavy-vehicle drivers, assessed their effects, and ranked them according to extent of influence by using statistical analysis and the technique for order of preference by similarity to ideal solution (TOPSIS). Data were collected through interviews guided by a questionnaire, through which three main categories of factors that contribute to crashes caused by fatigue and sleepiness were discussed. These categories are (I) human, (II) road and environmental conditions, and (III) vehicle-related factors. The results showed that human and road and environmental conditions exert the strongest and weakest effects, respectively. The statistical and TOPSIS results revealed that the first four factors that exert the strongest effects are inappropriate behaviors of passengers and goods owners, non-standard roads, inappropriate behaviors of police, and economic problems of heavy-vehicle drivers.

中文翻译：

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疲劳风险管理：使用 TOPSIS 和统计分析对影响重型车辆驾驶员疲劳和困倦程度的因素进行评估和排序

这项描述性分析研究确定了影响重型车辆驾驶员疲劳和困倦程度的因素，评估了它们的影响，并通过使用统计分析和根据与理想解决方案相似度的偏好排序技术，根据影响程度对它们进行了排序。托普西斯）。数据是通过问卷引导的访谈收集的，通过问卷讨论了导致疲劳和困倦导致撞车的三类主要因素。这些类别是 (I) 人类，(II) 道路和环境条件，以及 (III) 车辆相关因素。结果表明，人和道路和环境条件分别发挥最强和最弱的影响。