Effective Alerts for Autonomous Solutions to Aid Drivers Experiencing Medical Anomalies

With autonomous vehicle technology on the rise, there are many questions about its possible applications and its procedures. In this study there was a focus on using autonomous technology to aid in protect drivers with certain medical conditions that can cause unsafe driving conditions. A scenario was created for this study, which was explained to users. This included a vehicle being pulled over using autonomous methods when a medical anomaly is detected. This scenario allows the examination of the preferred alarm systems of users to alert them of self-driving technology during a medical emergency. To determine this, a user study was conducted to evaluate the preference which included 21 participants. Volunteers in this study drove a simulation and were presented with several different icons and alarms based upon vehicle standards. Results showed that an alarm tone was more noticeable and comprehendible than a blinking effect. Also, a preferred textual icon was found among the participants.

• Record URL:
  https://doi.org/10.1007/978-3-030-50523-3
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030505226
• Supplemental Notes:
  • © Springer Nature Switzerland AG 2020.
• Corporate Authors:

  Springer International Publishing

  ,    
• Authors:
  • Havro, Mariah
  • Morelli, Tony
• Conference:
  • 22nd HCI International Conference (HCII 2020)
  • Location: Copenhagen , Denmark
  • Date: 2020-7-19 to 2020-7-24
• Publication Date: 2020-7

Language

• English

Media Info

• Media Type: Web
• Edition: 1
• Features: References;
• Pagination: pp 279-288
• Monograph Title: HCI in Mobility, Transport, and Automotive Systems. Automated Driving and In-Vehicle Experience Design: Second International Conference, MobiTAS 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I
• Serial:
  • Lecture Notes in Computer Science
  • Volume: 12212
  • Publisher: Springer Cham
  • ISSN: 0302-9743
  • Serial URL: https://www.springer.com/series/558

Subject/Index Terms

• TRT Terms: Alarm systems; Autonomous vehicles; Consumer preferences; Diseases and medical conditions; Driving simulators
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01884475
• Record Type: Publication
• ISBN: 9783030505226
• Files: TRIS
• Created Date: Jun 2 2023 12:14PM