The impact of different human-machine interface feedback modalities on older participants' user experience of CAVs in a simulator environment

Eimontaite, Iveta; Voinescu, Alexandra; Alford, Chris; Caleb-Solly, Praminda; Morgan, Phillip

Abstract

Rapidly developing Autonomous Vehicle (AV) technology has potential to provide solutions to some of the aging population challenges, such as social isolation resulting from an inability to be independently mobile. However for AVs success, users' acceptance is essential. Fifteen participants (M 70 years) participated in an autonomous driving simulator trial with voice-based CAV status feedback in a decision-making scenario-whether to pick up a friend on the way. The within-subject conditions/journeys were: Audio feedback (Audio)/Pick-Up; Audio/No-PickUp ; No-Audio/Pick-Up. Additionally, the effect of feedback during different external journey conditions was also considered, resulting in two between-subjects conditions-day and night travel. Participants physiological, cognitive and affective measures show greater situational awareness and work-load ratings in the No-Audio/Pick-Up condition with increased Post-trial trust rating and overall higher positive affect. These results indicate that the greatest concentration was required in the no-sound condition, suggesting that sound/multimodal feedback improved ease of operation and journey experience.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: International Conference on Applied Human Factors and Ergonomics
• Start Date: Jul 24, 2019
• End Date: Jul 28, 2019
• Acceptance Date: Jun 6, 2019
• Online Publication Date: Jun 6, 2019
• Publication Date: Aug 1, 2019
• Deposit Date: Mar 19, 2020
• Publicly Available Date: Jun 7, 2020
• Publisher: Springer Verlag
• Volume: 964
• Pages: 120-132
• Series Title: Advances in Intelligent Systems and Computing
• Book Title: Proceedings of the AHFE 2019 International Conference on Human Factors in Transportation
• ISBN: 9783030205027
• DOI: https://doi.org/10.1007/978-3-030-20503-4_11
• Public URL: https://uwe-repository.worktribe.com/output/5694762