Assessing Alternative Approaches for Conveying Automated Vehicle \u2018Intentions' [supporting datasets]

US Transportation Collectionhttps://doi.org/10.15787/VTT1/Z5DZAJ2020ZIPDatasetVirginia Tech Transportation InstituteSafety through Disruption (Safe-D) University Transportation Center (UTC)United States. Department of Transportation. University Transportation Centers (UTC) ProgramUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyVirginia Tech Transportation InstituteSafety through Disruption (Safe-D) University Transportation Center (UTC)Texas A&M Transportation InstituteUnited StatesAutonomous vehiclesData displaysField testsHuman machine systemsPassengersTrust (Psychology)User interfaces (Computer science)GuidelinesReportsBrochuresMarketingCommunication03-08269A3551747115/Project 03-082One of the biggest highly automated vehicle (HAV) market barriers may be a lack of user trust in the automated driving system itself. Research has shown that this lack of faith in the system primarily stems from a lack of system transparency while the vehicle is in motion\u2014users are not informed how the car will react in an upcoming scenario\u2014and not having an effective way to control the vehicle in the event of a system failure. This problem is particularly prevalent in public transit or ridesharing applications, where HAVs are expected to first appear and where the user has less training on and control over the vehicle. To improve user trust and perceptions of comfort and safety, this study evaluated human-machine interface (HMI) systems, focused on visual and auditory displays, to better relay the perceived driving environment and the automated vehicle \u201cintentions\u201d to the user. These HMI systems were then implemented into a HAV developed at the Virginia Tech Transportation Institute and tested with volunteer participants on the Smart Roads.109