{"title":"How Human Drivers Can Benefit From Collective Perception: A User Study","authors":"Keno Garlichs, Maximilian Huber, Lars C. Wolf","doi":"10.1109/MITS.2023.3263890","DOIUrl":null,"url":null,"abstract":"Collective perception is one of the key ideas of vehicular networking and allows the exchange of data about perceived objects. However, unlike autonomous driving systems, human drivers cannot screen large numbers of objects to judge their dangerousness. An assistance system in the vehicle, therefore, must do this job. This article shows a concept for a human–machine interface that could be used to warn the driver in case such a system detects an actually dangerous object. A user study in a driving simulator was performed to evaluate its potential to prevent accidents. Eye-tracking glasses were used to analyze the driver’s gaze during different types of situations. Furthermore, the participants’ subjective experience was evaluated with a questionnaire. Results show that drivers trust the system and brake earlier and with more control due to the warnings, and ultimately, the majority of accidents could be avoided thanks to the warnings.","PeriodicalId":48826,"journal":{"name":"IEEE Intelligent Transportation Systems Magazine","volume":"15 1","pages":"25-35"},"PeriodicalIF":4.3000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Transportation Systems Magazine","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/MITS.2023.3263890","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Collective perception is one of the key ideas of vehicular networking and allows the exchange of data about perceived objects. However, unlike autonomous driving systems, human drivers cannot screen large numbers of objects to judge their dangerousness. An assistance system in the vehicle, therefore, must do this job. This article shows a concept for a human–machine interface that could be used to warn the driver in case such a system detects an actually dangerous object. A user study in a driving simulator was performed to evaluate its potential to prevent accidents. Eye-tracking glasses were used to analyze the driver’s gaze during different types of situations. Furthermore, the participants’ subjective experience was evaluated with a questionnaire. Results show that drivers trust the system and brake earlier and with more control due to the warnings, and ultimately, the majority of accidents could be avoided thanks to the warnings.
期刊介绍:
The IEEE Intelligent Transportation Systems Magazine (ITSM) publishes peer-reviewed articles that provide innovative research ideas and application results, report significant application case studies, and raise awareness of pressing research and application challenges in all areas of intelligent transportation systems. In contrast to the highly academic publication of the IEEE Transactions on Intelligent Transportation Systems, the ITS Magazine focuses on providing needed information to all members of IEEE ITS society, serving as a dissemination vehicle for ITS Society members and the others to learn the state of the art development and progress on ITS research and applications. High quality tutorials, surveys, successful implementations, technology reviews, lessons learned, policy and societal impacts, and ITS educational issues are published as well. The ITS Magazine also serves as an ideal media communication vehicle between the governing body of ITS society and its membership and promotes ITS community development and growth.