{"title":"Effect of riding experience and HMI on users’ trust and riding comfort in fully driverless autonomous vehicles: An on-road study","authors":"Weiyin Xie , Zhenyu Wang , Dengbo He","doi":"10.1016/j.apergo.2025.104580","DOIUrl":null,"url":null,"abstract":"<div><div>The wide adoption of autonomous vehicles (AVs) or robot taxis relies on technological advancements and public acceptance, which can be influenced by users’ trust in AVs and comfort during rides. Among the influential factors of riding comfort, motion sickness (MS) has attracted lots of attention in previous research, and both trust and MS have been found to be associated with human-machine interface (HMI) designs in AVs. However, previous research on trust and MS in AVs predominantly utilized driving simulations or \"Wizard of Oz\" methods, which failed to introduce risk and realistic vehicle motions, potentially introducing bias to conclusions. For the first time, our study investigated the impact of displaying the dynamic path trajectories of AVs on passengers' perceptions of system transparency, trust, and MS in a commercially running AV. The results from 16 participants and 32 rides revealed limited effects of the dynamic path trajectory on trust, and a discernible but statistically non-significant trend in MS alleviation. Further, we found that the initial riding experience was more important in trust enhancement than subsequent rides. These results provide insights into future HMI design in robot taxis and suggest directions for future research in trust enhancement and MS alleviation in AVs.</div></div>","PeriodicalId":55502,"journal":{"name":"Applied Ergonomics","volume":"129 ","pages":"Article 104580"},"PeriodicalIF":3.1000,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Ergonomics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0003687025001164","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
The wide adoption of autonomous vehicles (AVs) or robot taxis relies on technological advancements and public acceptance, which can be influenced by users’ trust in AVs and comfort during rides. Among the influential factors of riding comfort, motion sickness (MS) has attracted lots of attention in previous research, and both trust and MS have been found to be associated with human-machine interface (HMI) designs in AVs. However, previous research on trust and MS in AVs predominantly utilized driving simulations or "Wizard of Oz" methods, which failed to introduce risk and realistic vehicle motions, potentially introducing bias to conclusions. For the first time, our study investigated the impact of displaying the dynamic path trajectories of AVs on passengers' perceptions of system transparency, trust, and MS in a commercially running AV. The results from 16 participants and 32 rides revealed limited effects of the dynamic path trajectory on trust, and a discernible but statistically non-significant trend in MS alleviation. Further, we found that the initial riding experience was more important in trust enhancement than subsequent rides. These results provide insights into future HMI design in robot taxis and suggest directions for future research in trust enhancement and MS alleviation in AVs.
期刊介绍:
Applied Ergonomics is aimed at ergonomists and all those interested in applying ergonomics/human factors in the design, planning and management of technical and social systems at work or leisure. Readership is truly international with subscribers in over 50 countries. Professionals for whom Applied Ergonomics is of interest include: ergonomists, designers, industrial engineers, health and safety specialists, systems engineers, design engineers, organizational psychologists, occupational health specialists and human-computer interaction specialists.