{"title":"采用视觉注意任务和眼动追踪研究接管前资源投入对有条件自动驾驶注意恢复的影响。","authors":"Jinzhen Dou, Chang Xu, Wenyu Wu, Chengqi Xue, Shanguang Chen","doi":"10.1080/15389588.2024.2427865","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Attention forms the foundation for the formation of situation awareness. Low situation awareness can lead to driving performance decline, which can be dangerous in driving. The goal of this study is to investigate how different types of pre-takeover tasks, involving cognitive, visual and physical resources engagement, as well as individual attentional function, affect driver's attention restoration in conditionally automated driving.</p><p><strong>Methods: </strong>A two-phase study was conducted. In phase one, a visual attentional task was employed to measure the attentional function of driver. In phase two, a driving simulator experiment was conducted, where participants experienced a typical sequence of automated driving, takeover and manual driving. Three pre-takeover tasks were designed to divert drivers' attentional resources, including a visual-cognitive task, a visual-physical task, and a monitoring task (control group). Eye-tracking metrics, including pupil and gaze behavior, along with driving behavior, were assessed as dependent variables.</p><p><strong>Results: </strong>The visual-cognitive task showed the highest percentage of pupil dilation and significantly increased participant's response time, but it also had a positive effect on subsequent attention restoration. Moreover, the attentional task scores were positively correlated with horizontal gaze scanning and negatively correlated with takeover response time.</p><p><strong>Conclusions: </strong>Pre-takeover tasks with cognitive resource engagement proves to be superior for attention restoration in conditionally automated driving. The drivers with better attentional function are able to reduce recovering time. These findings make it possible to predict drivers' attentional state by identifying type of pre-takeover tasks in conditionally automated vehicles. Based on this, the attentive user interfaces could be adaptively adjusted to provide valuable cues, ensuring a safe transition.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using a visual attentional task and eye-tracking to investigate the effects of pre-takeover resource engagement on attention restoration in conditionally automated driving.\",\"authors\":\"Jinzhen Dou, Chang Xu, Wenyu Wu, Chengqi Xue, Shanguang Chen\",\"doi\":\"10.1080/15389588.2024.2427865\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Attention forms the foundation for the formation of situation awareness. Low situation awareness can lead to driving performance decline, which can be dangerous in driving. The goal of this study is to investigate how different types of pre-takeover tasks, involving cognitive, visual and physical resources engagement, as well as individual attentional function, affect driver's attention restoration in conditionally automated driving.</p><p><strong>Methods: </strong>A two-phase study was conducted. In phase one, a visual attentional task was employed to measure the attentional function of driver. In phase two, a driving simulator experiment was conducted, where participants experienced a typical sequence of automated driving, takeover and manual driving. Three pre-takeover tasks were designed to divert drivers' attentional resources, including a visual-cognitive task, a visual-physical task, and a monitoring task (control group). Eye-tracking metrics, including pupil and gaze behavior, along with driving behavior, were assessed as dependent variables.</p><p><strong>Results: </strong>The visual-cognitive task showed the highest percentage of pupil dilation and significantly increased participant's response time, but it also had a positive effect on subsequent attention restoration. Moreover, the attentional task scores were positively correlated with horizontal gaze scanning and negatively correlated with takeover response time.</p><p><strong>Conclusions: </strong>Pre-takeover tasks with cognitive resource engagement proves to be superior for attention restoration in conditionally automated driving. The drivers with better attentional function are able to reduce recovering time. These findings make it possible to predict drivers' attentional state by identifying type of pre-takeover tasks in conditionally automated vehicles. Based on this, the attentive user interfaces could be adaptively adjusted to provide valuable cues, ensuring a safe transition.</p>\",\"PeriodicalId\":54422,\"journal\":{\"name\":\"Traffic Injury Prevention\",\"volume\":\" \",\"pages\":\"1-9\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Traffic Injury Prevention\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/15389588.2024.2427865\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traffic Injury Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15389588.2024.2427865","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Using a visual attentional task and eye-tracking to investigate the effects of pre-takeover resource engagement on attention restoration in conditionally automated driving.
Objective: Attention forms the foundation for the formation of situation awareness. Low situation awareness can lead to driving performance decline, which can be dangerous in driving. The goal of this study is to investigate how different types of pre-takeover tasks, involving cognitive, visual and physical resources engagement, as well as individual attentional function, affect driver's attention restoration in conditionally automated driving.
Methods: A two-phase study was conducted. In phase one, a visual attentional task was employed to measure the attentional function of driver. In phase two, a driving simulator experiment was conducted, where participants experienced a typical sequence of automated driving, takeover and manual driving. Three pre-takeover tasks were designed to divert drivers' attentional resources, including a visual-cognitive task, a visual-physical task, and a monitoring task (control group). Eye-tracking metrics, including pupil and gaze behavior, along with driving behavior, were assessed as dependent variables.
Results: The visual-cognitive task showed the highest percentage of pupil dilation and significantly increased participant's response time, but it also had a positive effect on subsequent attention restoration. Moreover, the attentional task scores were positively correlated with horizontal gaze scanning and negatively correlated with takeover response time.
Conclusions: Pre-takeover tasks with cognitive resource engagement proves to be superior for attention restoration in conditionally automated driving. The drivers with better attentional function are able to reduce recovering time. These findings make it possible to predict drivers' attentional state by identifying type of pre-takeover tasks in conditionally automated vehicles. Based on this, the attentive user interfaces could be adaptively adjusted to provide valuable cues, ensuring a safe transition.
期刊介绍：
The purpose of Traffic Injury Prevention is to bridge the disciplines of medicine, engineering, public health and traffic safety in order to foster the science of traffic injury prevention. The archival journal focuses on research, interventions and evaluations within the areas of traffic safety, crash causation, injury prevention and treatment.
General topics within the journal''s scope are driver behavior, road infrastructure, emerging crash avoidance technologies, crash and injury epidemiology, alcohol and drugs, impact injury biomechanics, vehicle crashworthiness, occupant restraints, pedestrian safety, evaluation of interventions, economic consequences and emergency and clinical care with specific application to traffic injury prevention. The journal includes full length papers, review articles, case studies, brief technical notes and commentaries.
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