Driver State Detection Using Dual Thresholds for Undrivability
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Solution Overview
Problem
Existing abnormality detection devices for drivers cannot effectively distinguish between a warning state indicating a potential undrivable condition and an actual abnormal state where the driver is undrivable.
Innovation Solution
An abnormality detection device that includes a control unit configured to detect a warning state and an abnormal state based on acquired driver information, using a combination of image data from a camera, heart rate data from a heart rate meter, and voice data from a microphone, to differentiate between the two states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single detection threshold is used to determine driver undrivability, then the detection process is simple, but the system cannot distinguish between warning states and abnormal states
Solution Approach 1:
The patent divides the driver state detection into two distinct thresholds: a first threshold for detecting warning states and a second threshold for detecting abnormal states. This segmentation allows the system to differentiate between gradual fatigue accumulation (warning state) and immediate undrivability (abnormal state), resolving the contradiction by enabling precise state differentiation while maintaining relatively simple detection logic through threshold comparison.
Solution Approach 2:
The patent changes the detection parameter from a single undrivability threshold to multiple thresholds (first threshold and second threshold) that represent different stages of driver fatigue. By introducing parameter variation in the detection criteria, the system can distinguish between warning and abnormal states, improving measurement precision without requiring complex multi-dimensional analysis.
2Measurement precision
If multiple detection thresholds are implemented to distinguish warning and abnormal states, then state differentiation precision improves, but detection system complexity increases
Solution Approach 1:
The detection system is segmented into two distinct threshold levels: a first threshold that triggers warning state detection and a second threshold that triggers abnormal state detection. This segmentation enables precise differentiation between warning and abnormal states while keeping the detection logic relatively simple through straightforward threshold comparison operations.
Solution Approach 2:
The system employs parameter changes by implementing multiple detection thresholds (first threshold and second threshold) that correspond to different stages of driver fatigue. This approach improves measurement precision by enabling state differentiation while avoiding the complexity of multi-dimensional analysis through the use of comparable threshold parameters.
3Reliability
If only undrivable state detection is implemented, then the detection system is simple, but timely warning cannot be provided to prevent accidents
Solution Approach 1:
The patent implements preliminary action by detecting warning states before the driver reaches an undrivable state. The first threshold is set to trigger a warning notification when the driver approaches fatigue-induced undrivability, allowing timely intervention (such as taking a break or switching drivers) to prevent accidents. This preliminary detection enhances accident prevention capability while maintaining simple detection logic through threshold comparison.
Solution Approach 2:
The system provides beforehand cushioning by introducing a warning state that acts as a buffer before the driver reaches an undrivable state. The first threshold creates a safety margin that allows preventive measures to be taken before actual undrivability occurs, thereby enhancing reliability for accident prevention without requiring complex predictive modeling.
4Reliability
If warning state detection is added to abnormal state detection, then accident prevention capability improves, but detection system complexity increases
Solution Approach 1:
The detection system is segmented into two functional components: a first threshold for warning state detection and a second threshold for abnormal state detection. This segmentation enables the system to provide both timely warnings and accurate undrivability detection, improving accident prevention capability while maintaining relatively simple detection logic through threshold-based classification.
Solution Approach 2:
The system uses parameter changes by implementing multiple detection thresholds that correspond to different fatigue stages. The first threshold parameter triggers warning notifications, while the second threshold parameter triggers abnormal state detection. This approach improves reliability for accident prevention by enabling early warning while avoiding the complexity of multi-dimensional analysis through comparable threshold parameters.
Data Source
AI summary
An abnormality detection device includes a control unit configured to detect, based on information regarding a driver of a vehicle that has been acquired by an input unit, a warning state indicating a warning that the driver is to become undrivable, and an abnormal state indicating that the driver is undrivable. The input unit includes a camera configured to generate image data, and the information is the image data obtained by capturing an image of the driver by the camera.