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Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological Signals.

Timotej GrudenSašo TomažičGrega Jakus
Published in: Sensors (Basel, Switzerland) (2024)
In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads.
Keyphrases
  • heart rate
  • deep learning
  • high throughput
  • blood pressure
  • artificial intelligence
  • drug induced