{"title":"当多则少:在第三级自动驾驶汽车中寻找智能代理透明度的最佳平衡点","authors":"Jing Zang, Myounghoon Jeon","doi":"10.1016/j.ijhcs.2024.103384","DOIUrl":null,"url":null,"abstract":"<div><div>In automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to drivers’ perception, situation awareness, and driving performance. Our experiment focused on IVIA's transparency regarding information level and reliability on drivers’ perception and performance in level 3 automated vehicles. A 3 × 2 mixed factorial design was used in this study, with transparency (low, medium, high) as a between-subject variable and reliability (high vs. low) as a within-subjects variable. Forty-eight participants were recruited. Results suggested that transparency influenced drivers’ takeover time, lane keeping, and jerk. The high-reliability agent was associated with a higher perception of system accuracy and response speed and resulted in a longer takeover time than the low-reliability agent. Particularly, participants in medium transparency showed higher cognitive trust, lower workload, and higher situation awareness only when system reliability was high. Our findings can contribute to the advancement of intelligent agent transparency design in automated vehicles.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"193 ","pages":"Article 103384"},"PeriodicalIF":5.3000,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"When more is less: Finding the optimal balance of intelligent agents’ transparency in level 3 automated vehicles\",\"authors\":\"Jing Zang, Myounghoon Jeon\",\"doi\":\"10.1016/j.ijhcs.2024.103384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to drivers’ perception, situation awareness, and driving performance. Our experiment focused on IVIA's transparency regarding information level and reliability on drivers’ perception and performance in level 3 automated vehicles. A 3 × 2 mixed factorial design was used in this study, with transparency (low, medium, high) as a between-subject variable and reliability (high vs. low) as a within-subjects variable. Forty-eight participants were recruited. Results suggested that transparency influenced drivers’ takeover time, lane keeping, and jerk. The high-reliability agent was associated with a higher perception of system accuracy and response speed and resulted in a longer takeover time than the low-reliability agent. Particularly, participants in medium transparency showed higher cognitive trust, lower workload, and higher situation awareness only when system reliability was high. Our findings can contribute to the advancement of intelligent agent transparency design in automated vehicles.</div></div>\",\"PeriodicalId\":54955,\"journal\":{\"name\":\"International Journal of Human-Computer Studies\",\"volume\":\"193 \",\"pages\":\"Article 103384\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human-Computer Studies\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071581924001678\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581924001678","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
When more is less: Finding the optimal balance of intelligent agents’ transparency in level 3 automated vehicles
In automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to drivers’ perception, situation awareness, and driving performance. Our experiment focused on IVIA's transparency regarding information level and reliability on drivers’ perception and performance in level 3 automated vehicles. A 3 × 2 mixed factorial design was used in this study, with transparency (low, medium, high) as a between-subject variable and reliability (high vs. low) as a within-subjects variable. Forty-eight participants were recruited. Results suggested that transparency influenced drivers’ takeover time, lane keeping, and jerk. The high-reliability agent was associated with a higher perception of system accuracy and response speed and resulted in a longer takeover time than the low-reliability agent. Particularly, participants in medium transparency showed higher cognitive trust, lower workload, and higher situation awareness only when system reliability was high. Our findings can contribute to the advancement of intelligent agent transparency design in automated vehicles.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
...