{"title":"Awakening the Disengaged: Can Driving-Related Prompts Engage Drivers in Partial Automation?","authors":"Xiaolu Bai, Jing Feng","doi":"10.1177/00187208251314248","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study explores the effectiveness of conversational prompts on enhancing driver monitoring behavior and takeover performance in partially automated driving under two non-driving-related task (NDRT) scenarios with varying workloads.</p><p><strong>Background: </strong>Driver disengagement in partially automated driving is a serious safety concern. Intermittent conversational prompts that require responses may be a solution. However, existing literature is limited with inconsistent findings. There is little consideration of NDRTs as an important context, despite their ubiquitous involvement. A method is also lacking to measure driver engagement at the cognitive level, beyond manual and visual engagements.</p><p><strong>Methods: </strong>Participants operated a partially automated vehicle in a simulator across six predefined drives. In each drive, participants either received driving-related prompts, daily-conversation prompts, or no prompts, with or without a takeover notification. The first experiment instructed participants to engage in NDRTs at their choice and the second experiment incentivized solving demanding anagrams with monetary rewards.</p><p><strong>Results: </strong>When participants were voluntarily engaged in NDRTs, answering driving-related prompts and receiving takeover notifications improved their monitoring behavior and takeover performance. However, when participants were involved in the more demanding and incentivized NDRT, answering prompts had little effect.</p><p><strong>Conclusion: </strong>The study supports the importance of both maintaining appropriate workload and processing driving-related information during partially automated driving. Driving-related prompts improve driver engagement and takeover performance, but they are not robust enough to compete with NDRTs that have high motivational appeals and cognitive demands.</p><p><strong>Application: </strong>The design of driver engagement tools should consider the workload and information processing mechanisms.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208251314248"},"PeriodicalIF":2.9000,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Factors","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/00187208251314248","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: This study explores the effectiveness of conversational prompts on enhancing driver monitoring behavior and takeover performance in partially automated driving under two non-driving-related task (NDRT) scenarios with varying workloads.
Background: Driver disengagement in partially automated driving is a serious safety concern. Intermittent conversational prompts that require responses may be a solution. However, existing literature is limited with inconsistent findings. There is little consideration of NDRTs as an important context, despite their ubiquitous involvement. A method is also lacking to measure driver engagement at the cognitive level, beyond manual and visual engagements.
Methods: Participants operated a partially automated vehicle in a simulator across six predefined drives. In each drive, participants either received driving-related prompts, daily-conversation prompts, or no prompts, with or without a takeover notification. The first experiment instructed participants to engage in NDRTs at their choice and the second experiment incentivized solving demanding anagrams with monetary rewards.
Results: When participants were voluntarily engaged in NDRTs, answering driving-related prompts and receiving takeover notifications improved their monitoring behavior and takeover performance. However, when participants were involved in the more demanding and incentivized NDRT, answering prompts had little effect.
Conclusion: The study supports the importance of both maintaining appropriate workload and processing driving-related information during partially automated driving. Driving-related prompts improve driver engagement and takeover performance, but they are not robust enough to compete with NDRTs that have high motivational appeals and cognitive demands.
Application: The design of driver engagement tools should consider the workload and information processing mechanisms.
期刊介绍：
Human Factors: The Journal of the Human Factors and Ergonomics Society publishes peer-reviewed scientific studies in human factors/ergonomics that present theoretical and practical advances concerning the relationship between people and technologies, tools, environments, and systems. Papers published in Human Factors leverage fundamental knowledge of human capabilities and limitations – and the basic understanding of cognitive, physical, behavioral, physiological, social, developmental, affective, and motivational aspects of human performance – to yield design principles; enhance training, selection, and communication; and ultimately improve human-system interfaces and sociotechnical systems that lead to safer and more effective outcomes.
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