The Dynamics of Attention Across Automated and Manual Driving Modes: A Driving Simulation Study

Area of Science:

• Human-Computer Interaction
• Automotive Safety
• Cognitive Psychology

Background:

• Automated vehicles (AVs) integration raises safety concerns, especially driver re-engagement during mode transitions.
• Driver over-reliance on automation and attention allocation are critical for safety during automated driving.
• Understanding dynamic visual attention is crucial for mitigating risks associated with AVs.

Purpose of the Study:

• To explore driver attention dynamics across various zones (road, mirrors, center stack, instrument cluster) in different automated vehicle (AV) driving modes.
• To analyze how visual attention allocation changes during manual, automated, and transition driving phases.
• To provide insights for designing AV interfaces that support driver attention and safety.

Main Methods:

• Utilized a high-fidelity driving simulation with eye-tracking technology.
• Measured fixation duration, fixation count, and time to first fixation (TFF) across driving modes.
• Analyzed sustained attention and attentional reallocation/latency to different areas of interest (AOIs).

Main Results:

• Driver attention allocation is significantly dependent on the driving mode.
• Manual mode shows consistent road focus; automated mode exhibits prolonged center stack attention.
• Transition phases reveal dynamic attention shifts between environmental and technological elements.

Conclusions:

• Driver attention patterns are mode-dependent, influencing interaction with automated vehicle systems.
• Findings inform the design of center stacks and driver training programs to enhance attention and safety.
• Optimizing information presentation based on driving context can improve driver-vehicle interaction and transition safety.