Vehicle Drowsiness Detection via Multi-Sensor Validity Weighting
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Solution Overview
Problem
Current driver drowsiness detection methods in vehicles are not reliable due to inconsistencies in drowsiness parameter determination and validation, leading to potential false results from individual drowsiness-detection devices with varying accuracy.
Innovation Solution
A method that combines multiple drowsiness-detection devices' results, validates their indicators, and weights them based on validity to determine a comprehensive drowsiness signal, incorporating head, steering, and driving-environment signals, with a control unit implementing this method to output a meaningful and reliable drowsiness assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple drowsiness-detection devices are used to improve detection reliability, then the reliability of drowsiness detection is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple drowsiness-detection devices (camera-based eye tracking, steering behavior analysis, driving pattern monitoring) into a unified detection system that integrates their outputs through a control unit, achieving improved reliability while managing complexity through systematic integration
2Measurement precision
If validity validation of indicator signals is implemented to improve accuracy, then the measurement precision is improved, but the processing time increases
Solution Approach 1:
The system performs validity checks on indicator signals in advance before final drowsiness assessment, pre-validating the reliability of each detection device's output so that during critical assessment moments, only pre-validated data needs to be processed, reducing real-time processing time
3Measurement precision
If weighting based on validity is applied to improve detection accuracy, then the measurement precision is improved, but the computational complexity increases
Solution Approach 1:
The control unit applies different weighting factors to indicator signals based on their individual validity assessments, giving higher weight to more reliable detection devices and lower weight to less reliable ones, thereby improving overall assessment accuracy through differentiated processing
Data Source
AI summary
A method for detecting drowsiness of a driver for a driver assistance system of a vehicle includes reading in at least a first indicator signal that represents a first drowsiness parameter of the driver determined by a first drowsiness-detection device of the vehicle, and a second indicator signal that represents a second drowsiness parameter of the driver determined by a second drowsiness-detection device of the vehicle, and optionally a third indicator signal that represents a third drowsiness parameter of the driver determined by a third drowsiness-detection device of the vehicle; ascertaining validities of the indicator signals; and determining a drowsiness signal that represents the detected drowsiness of the driver utilizing the indicator signals and the validities.