GEORGIA INSTITUTE OF TECHNOLOGY
Under the provisions of the regulations for the degree
MASTER OF INDUSTRIAL DESIGN
on
Friday, November 22, 2024
9:30 a.m. – 10:30 p.m. EST
East Architecture room 214
Online Link:
teams.microsoft.com
Seryung Kim
will present a thesis defense entitled,
"Designing a Multimodal, Environmental Interface to Enhance Time-Based Urgency Perception of Takeover Requests and Understanding of Takeover Reasons in Semi-Autonomous Vehicles"
Advisor:
Dr. Yixiao Wang, Georgia Tech School of Industrial Design
Committee:
Prof. Tim Purdy, Georgia Tech School of Industrial Design
Prof. David Lynn, Georgia Tech School of Industrial Design
Dr. Mengyao Li, Georgia Tech School of Psychology
Faculty and students are invited to attend this presentation.
Abstract
In the field of Semi-Autonomous Vehicles (SAVs), or partially automated vehicles, ensuring that drivers can better understand and respond to Take Over Requests (TORs) is essential for road safety. This thesis explores a new TOR interface design, called the Context-Aware Adaptive (CAA) design, which uses both visual and auditory cues to improve drivers’ awareness of urgency and understanding of takeover reasons. Using a Research through Design (RtD) methodology and a Mixed Methods approach (quantitative and qualitative), four dynamic driving scenarios of varying lengths and takeover reasons were simulated in Virtual Reality (VR) to test two TOR designs: the CAA design and a Baseline design. Both designs were evaluated on usability and efficacy with 25 participants, using the Situation Awareness Global Assessment Technique (SAGAT), which is a freeze-probe technique, to assess people's perceived level of urgency at three critical time points (T1, T2, and T3). Results showed that the CAA design helped drivers better perceive the gradual change of urgency levels and understand takeover reasons compared to the Baseline design. This research contributes to Human-Machine Interaction (HMI) for SAVs, suggesting that adaptive, multimodal TOR alerts can improve the dynamic communication between SAVs and drivers, potentially enhancing safety and user experience in automated systems.
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