Drifting, a skillful driving technique involving intentional traction loss and counter-steering, traditionally demands high-speed maneuvers under high-friction conditions, posing significant risks and fear for novices. Our study explores low-{\textmu} (low friction) emulation, simulating icy conditions to facilitate drift training at safer, lower speeds. This approach not only enhances safety and mitigates fear by reducing the required speed for drifting, but also extends the time for them to react. A between-group design was employed, comparing drift training outcomes between participants trained exclusively in higher-{\textmu} conditions (control group) and those who trained initially in lower-{\textmu} conditions before transitioning to higher-{\textmu} conditions (target group). The performance was assessed through the average distance of continuous sliding, along with subjective measures of motivation and workload. The results showed that the target group achieved greater slide distances in the retention session and reported higher scores on the positive intrinsic motivation factors, suggesting enhanced performance and engagement.

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https://hci.top/en/papers/auto_ui/168399/2024

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Paper Snapshot

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Source
AutoUI
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Year
2024
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No award tagged
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Authors
9 authors
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Subtopics
Automated Driving Interface & Takeover Design, Motion Sickness & Passenger Experience
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Professions
Autonomous Driving Engineers & Test Drivers
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Content Status
Abstract only
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