Joseba Sarabia;Myriam Vaca;Mauricio Marcano;Sergio Diaz;Joshué Pérez Rastelli;Asier Zubizarreta
{"title":"Haptic Icons: A Hands-On Approach to Haptic HMI in Automated Vehicles","authors":"Joseba Sarabia;Myriam Vaca;Mauricio Marcano;Sergio Diaz;Joshué Pérez Rastelli;Asier Zubizarreta","doi":"10.1109/OJITS.2025.3566589","DOIUrl":null,"url":null,"abstract":"This paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set of haptic notifications was designed based on input from the literature review, (2) These notifications were then tested in a driving simulator to identify the most effective options, and (3) The selected notifications were evaluated in a dynamic simulator under realistic conditions, including noise, vibration, and harshness (NVH). User studies were conducted at each phase to gather subjective metrics and validate the usability of the haptic feedback. The results demonstrate that specific haptic patterns enhance driver situational awareness and improve transitions between driving modes compared to conventional auditory signals, contributing to safer human-machine interaction in automated vehicles.","PeriodicalId":100631,"journal":{"name":"IEEE Open Journal of Intelligent Transportation Systems","volume":"6 ","pages":"673-691"},"PeriodicalIF":4.6000,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10982355","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10982355/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper examines the potential integration of haptic feedback on steering wheels for automated driving applications, with a particular focus on transitions between automated and manual modes, takeover requests, and warnings. An iterative, three-phase methodology was employed: (1) The initial set of haptic notifications was designed based on input from the literature review, (2) These notifications were then tested in a driving simulator to identify the most effective options, and (3) The selected notifications were evaluated in a dynamic simulator under realistic conditions, including noise, vibration, and harshness (NVH). User studies were conducted at each phase to gather subjective metrics and validate the usability of the haptic feedback. The results demonstrate that specific haptic patterns enhance driver situational awareness and improve transitions between driving modes compared to conventional auditory signals, contributing to safer human-machine interaction in automated vehicles.