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How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

机译:驱动程序如何使其行为对任务复杂性的变化进行调整:二次任务需求和道路环境因素的作用

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摘要

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition. (C) 2020 Elsevier Ltd. All rights reserved.
机译:本研究调查了不同任务复杂来源的影响,例如驾驶员行为的驾驶需求和二级任务要求。虽然有很多研究致力于了解二次任务需求或特定的道路交通环境对驾驶业绩的影响,但几乎没有关于司机如何使其行为对其组合业务的影响。本文旨在描述驾驶员行为,同时谈判不同的任务复杂来源,包括移动电话(即,呼叫和发短信)和不同的道路环境(即,直段,曲线,丘陵,隧道和山丘上)。进行了驾驶模拟器实验,以探索不同道路场景和不同类型的分心在驾驶时的影响。收集的数据用于通过具有重复措施的广义线性混合模型(GLMM)来估计驾驶行为。分析分为两个阶段。第一个旨在根据存在和缺乏行人和迎面而来的交通,不同的车道宽度和不同类型的分心来评估司机性能。第二阶段通过不同的道路几何和车道宽度和不同类型的分散方式进行驱动时分析了驾驶员行为。实验结果表明,在行人的存在和迎面而来的交通中,司机可能会在车道中的位置过正常。发现道路几何对驾驶员行为的影响大于移动电话分散的影响。发现弯曲的道路和山丘最多影响了优选的速度和横向位置。该研究的结果还表明,与认知分心和非分散情况相比,视觉手动分散注意力下的驾驶员具有更高的速度和横向位置的标准偏差。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Transportation research》 |2020年第5期|145-156|共12页
  • 作者单位

    Queensland Univ Technol QUT Inst Hlth & Biomed Innovat IHBI Brisbane Qld Australia|Queensland Univ Technol QUT Fac Hlth Ctr Accid Res & Rd Safety Queensland CARRS Q Brisbane Qld Australia;

    Queensland Univ Technol QUT Inst Hlth & Biomed Innovat IHBI Brisbane Qld Australia|Queensland Univ Technol QUT Fac Hlth Ctr Accid Res & Rd Safety Queensland CARRS Q Brisbane Qld Australia|Univ Norte Fac Engn Dept Ind Engn Barranquilla Colombia;

    Queensland Univ Technol QUT Inst Hlth & Biomed Innovat IHBI Brisbane Qld Australia|Queensland Univ Technol QUT Fac Hlth Ctr Accid Res & Rd Safety Queensland CARRS Q Brisbane Qld Australia;

  • 收录信息 美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Driver behaviour; Task complexity; Road environment; Road design; Road geometry; Mobile phone distraction; Cell phone; Smartphone;

    机译:司机行为;任务复杂;道路环境;道路设计;道路几何;手机分心;手机;智能手机;

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