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Cognitive States Matter: Design Guidelines for Driving Situation Awareness in Smart Vehicles
Daehee Park1, Wan Chul Yoon1, Uichin Lee1
1Graduate School of Knowledge Service Engineering, Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.
This study introduces cognitive state-aware design guidelines for situation awareness (SA) systems in driving. New guidelines significantly improved driver SA and decision-making performance by considering cognitive states.
Area of Science:
- Human-Computer Interaction
- Cognitive Psychology
- Automotive Safety
Background:
- Situation awareness (SA) is vital for safe driving, involving perception, comprehension, and projection of future states.
- Current SA design principles offer general guidance but lack detail for limited human cognitive capabilities.
- Future vehicles with advanced sensors will present complex information, challenging driver SA.
Purpose of the Study:
- To investigate key cognitive attributes influencing SA in driving: attention focus, mental model, workload, and memory.
- To identify eight critical cognitive states affecting driver SA.
- To propose cognitive state-aware SA design guidelines for effective information conveyance.
Main Methods:
- Investigated cognitive attributes and identified eight influential cognitive states.
- Developed cognitive state-aware SA design guidelines.
- Conducted controlled experiments comparing existing and new SA interfaces using SAGAT and DMQ.
Main Results:
- The new SA interface, designed with cognitive state-aware guidelines, led to significantly higher SA scores.
- Participants using the new interface exhibited improved decision-making performance.
- The study validates the effectiveness of considering cognitive states in SA system design.
Conclusions:
- Cognitive state-aware design guidelines enhance driver situation awareness and decision-making.
- These guidelines address limitations in current SA design principles for complex driving environments.
- Future research should explore further integration of cognitive states into automotive HMI design.
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