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首页> 外文期刊>Journal of Safety Research >Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran
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Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran

机译：驾驶员是否因数字广告牌而分心？基于自然驾驶研究数据的结构方程建模：以伊朗为例

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Introduction: Digital billboards (DBs) are a competing factor for attracting drivers' attention; evidence shows that DBs may cause crashes and vehicle conflicts because they catch drivers' attention. Because of the complexity of a system that includes road conditions, driver features, and environmental factors, it is simply not possible to identify relationships between these factors. Thus, the present study was conducted to provide a well-organized procedure to analyze the effects of DBs on drivers' behavior and measure factors responsible for drivers' distraction in Babol, Iran, as a case study. Method: Corresponding data were collected through a Naturalistic Driving Study (NDS) of 78 participants when facing DBs (1,326 samples). These data were analyzed by applying structural equation modeling (SEM) to concurrently recognize relationships between endogenous and exogenous variables. Human, environmental, and road factors were determined as exogenous latent variables in a model to evaluate their influences on drivers' distraction as an endogenous variable. Results: The results showed that road, environmental, and human factors reciprocally interact with drivers' distraction, although the estimated coefficient of human factors was more of a factor than that of the other groups. Furthermore, younger drivers, beginner drivers, and male drivers (as human factors); night and unclear weather like a rainy day (as environmental factors); and installing DBs at complicated traffic positions like near-intersections (as road factors) were determined to be the main factors that increase the possibility of drivers' distraction. Finally, model assessment was suggested using the goodness-of-fit indices. (C) 2019 National Safety Council and Elsevier Ltd. All rights reserved.
机译：简介：数字广告牌（DB）是吸引驾驶员注意力的竞争因素。证据表明，DB可能引起碰撞和车辆冲突，因为它们引起了驾驶员的注意。由于包括路况，驾驶员特征和环境因素在内的系统的复杂性，根本无法确定这些因素之间的关系。因此，本研究旨在提供一个井井有条的程序，以分析数据库对驾驶员行为的影响，并测量伊朗巴博尔驾驶员分心的因素，作为案例研究。方法：通过面对78名参与者的自然驾驶研究（NDS）收集了相应的数据（面对1,326个样本）。通过应用结构方程模型（SEM）分析这些数据，以同时识别内生变量和外生变量之间的关系。在模型中，将人，环境和道路因素确定为外源性潜在变量，以评估它们对驾驶员分心的影响（作为内源性变量）。结果：结果表明，道路，环境和人为因素与驾驶员的注意力分散程度相互影响，尽管人为因素的估计系数比其他组的影响更大。此外，年轻驾驶员，初学者驾驶员和男性驾驶员（作为人为因素）;夜晚和不明朗的天气（如雨天）（作为环境因素）;在靠近交叉路口的复杂交通位置（作为道路因素）安装DB被确定为增加驾驶员分心的可能性的主要因素。最后，建议使用拟合优度指标进行模型评估。 （C）2019国家安全委员会和Elsevier Ltd.保留所有权利。

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