Transportation Systems Engineering, Department of Civil Engineering, Indian Institute of Technology (IIT) Bombay, Powai, India.
Department of Industrial and Systems Engineering, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, India.
Int J Inj Contr Saf Promot. 2019 Dec;26(4):412-422. doi: 10.1080/17457300.2019.1660375. Epub 2019 Sep 2.
This study aims at capturing the influence of driver drowsiness on prevalence of traffic violations among long-haul truck drivers. The study is based on a roadside survey of 453 long-haul truck drivers, stopping at eateries and rest locations on highways connected to three Indian cities- Mumbai, Indore and Nagpur. The survey questionnaire was categorized into three sections: driver demographics, work-rest schedules and safety critical driver behavior (violations and lapses) in the last five years. The questions regarding unsafe driving practices like speeding, overtaking were combined to form a single factor 'violations' using Principal Component Analysis (PCA). A generalized linear model using negative binomial regression predicted young drivers (aged below 25 years), long working hours, insufficient sleeping hours, driving after mid-night, sleepiness on the wheel and frequent traffic violations as significant contributors of violations among the long-haul truck drivers.
本研究旨在探讨驾驶员困倦对长途卡车司机交通违法行为发生率的影响。该研究基于对在连接印度三个城市（孟买、印多尔和那格浦尔）的高速公路上的餐馆和休息区停靠的 453 名长途卡车司机进行的路边调查。调查问卷分为三部分：驾驶员人口统计学、工作-休息时间表以及过去五年的安全关键驾驶员行为（违规和失误）。使用主成分分析（PCA）将超速、超车等不安全驾驶行为的问题组合成一个单一因素“违规”。使用负二项回归的广义线性模型预测年轻驾驶员（年龄在 25 岁以下）、工作时间长、睡眠时间不足、午夜后驾驶、开车时困倦和频繁违反交通规则是长途卡车司机违规的重要因素。
