Assessing Alternative Approaches for Conveying Automated Vehicle ‘Intentions’ (03-082)

Project Description: One of the greatest barriers to the entry of highly automated vehicles (HAV) into the market is the lack of user trust in the vehicle. Research has shown that this lack of faith in the system primarily stems from a lack of system transparency while in motion (e.g., the user not being told how the car will react in a certain situation) and 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 and control over the vehicle. To improve user trust and perceptions of comfort and safety, this study developed human-machine interface (HMI) systems, focusing on visual and auditory displays, to better relay automated vehicle “intentions” and the perceived driving environment to the user. These HMI systems were then implemented into a HAV developed at the Virginia Tech Transportation Institute (VTTI) and tested with volunteer participants on the Smart Roads. Data Scope: The dataset includes participant responses to surveys (open-ended feedback, Likert-scale, yes/no answers) distributed during each testing session. Different surveys were distributed before the testing session began (“pre-session questionnaire”), after each trial (“post-trial questionnaire”), and after the surprise event (“post-surprise questionnaire”). Data Specification: See attached data dictionary pdf.