Driver glance behaviors and scanning patterns: Applying static and dynamic glance measures to the analysis of curve driving with secondary tasks

机译：驾驶员浏览行为和扫描模式：应用静态和动态浏览措施，以分析辅助任务驾驶曲线

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Abstract >Performing secondary tasks (or non‐driving‐related tasks) while driving on curved roads may be risky and unsafe. The purpose of this study was to explore whether driving safety in situations involving curved roads and secondary tasks can be evaluated using multiple measures of eye movement. We adopted Markov‐based transition algorithms (i.e., transition/stationary probabilities, entropy) to quantify drivers’ dynamic eye movement patterns, in addition to typical static visual measures, such as frequency and duration of glances. The algorithms were evaluated with data from an experiment (Jeong & Liu, 2019) involving multiple road curvatures and stimulus‐response secondary task types. Drivers were more likely to scan only a few areas of interest with a long duration in sharper curves. Total head‐down glance time was longer in less sharp curves in the experiment, but the probability of head‐down glances was higher in sharper curves over the long run. The number of reliable transitions between areas of interest varied with the secondary task type. The visual scanning patterns for visually undemanding tasks were as random as those for visually demanding tasks. Markov‐based measures of dynamic eye movements provided insights to better understand drivers’ underlying mental processes and scanning strategies, compared with typical static measures. The presented methods and results can be useful for in‐vehicle systems design and for further analysis of visual scanning patterns in the transportation domain. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><Abstract Type =“Main”XML：Lang =“en”> <标题类型=“main”>抽象</ title> >在弯曲道路上行驶时执行次要任务（或非驾驶相关的任务）可能是有风险和不安全的。本研究的目的是探讨是否可以使用多种眼球运动测量来评估涉及弯曲道路和二级任务的情况的驾驶安全性。除了典型的静态视觉测量之外，我们采用基于马尔可夫的转换算法（即转换/静止概率，熵）来量化驱动器的动态眼球运动模式，例如透气的频率和持续时间。通过从实验（Jeong＆amp; Liu，2019）的数据评估算法，涉及多种道路曲率和刺激反应二次任务类型。司机更有可能在较短的曲线中扫描几个兴趣区域。在实验中，总检测时间较低的曲线较低，但长远来看，在较短的曲线中，下降途径的可能性更高。利息区域之间的可靠转换的数量随二次任务类型而变化。视觉扫描模式的视觉扫描模式与视觉要求的任务一样随机。基于马尔可夫的动态眼动作措施提供了更好地了解驾驶员的潜在精神过程和扫描策略的见解，与典型的静态措施相比。呈现的方法和结果可用于车载系统设计，并进一步分析运输领域的视觉扫描模式。</ p> </摘要> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-32935/'>《Human Factors and Ergonomics in Manufacturing & Service Industries》</a> <b style="margin: 0 2px;">|</b><span>2019年第6期</span><b style="margin: 0 2px;">|</b><span>共10页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Jeong Heejin&option=202" target="_blank" rel="nofollow">Jeong Heejin;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Kang Ziho&option=202" target="_blank" rel="nofollow">Kang Ziho;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Liu Yili&option=202" target="_blank" rel="nofollow">Liu Yili;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Department of Mechanical and Industrial EngineeringUniversity of Illinois at ChicagoChicago Illinois;</p> <p>School of Industrial and Systems EngineeringUniversity of OklahomaNorman Oklahoma;</p> <p>Department of Industrial and Operations EngineeringUniversity of MichiganAnn Arbor Michigan;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/1730.html" title="机械制造工艺">机械制造工艺;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=driver glance&option=203" rel="nofollow">driver glance;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=driving safety&option=203" rel="nofollow">driving safety;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Markov chain&option=203" rel="nofollow">Markov chain;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=visual entropy&option=203" rel="nofollow">visual entropy;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=visual transition/stationary distribution&option=203" rel="nofollow">visual transition/stationary distribution;</a> </p> <div class="translation"> 机译：司机浏览;驾驶安全;马尔可夫链;视觉熵;视觉过渡/固定分布; 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