Steering Wheel Hand Detection Using 3D Image Classification
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Solution Overview
Problem
Current systems for determining whether a vehicle driver's hands are on the steering wheel are prone to false positives due to detection by other body parts or objects, lacking the ability to reliably distinguish hands from other elements.
Innovation Solution
A computer-implemented method using cameras to capture and process three-dimensional image data, allowing for the determination of hand cooperation with the steering element by analyzing pixel values and employing algorithms like particle filters and neural networks to differentiate hands from other objects and body parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If capacitive sensors or torque sensors inside the steering wheel are used to detect hand contact, then the system can detect human hands touching the steering wheel or force applied, but false positives occur when other objects or body parts contact the wheel
Solution Approach 1:
The patent introduces an intermediary classification system that processes sensor signals before final detection. Multiple sensor types (capacitive, torque, pressure) are combined and processed through classification algorithms that distinguish hand characteristics from other objects or body parts, reducing false positives while maintaining detection sensitivity
Solution Approach 2:
The system dynamically adjusts detection parameters such as sensitivity thresholds, capacitance ranges, and torque thresholds based on driving conditions and sensor calibration. This allows the system to adapt to different scenarios and reduce false detections while maintaining accurate hand detection across varying operational contexts
2Measurement precision
If gesture tracking or body posture measurement systems are used to monitor driver hands, then hand position can be tracked, but the systems cannot reliably distinguish hands from other body parts or objects
Solution Approach 1:
The detection system divides the monitoring task into multiple independent sensor channels (capacitive sensing, torque sensing, pressure sensing) that each provide specific information. By segmenting the detection function across multiple sensor types, the system can cross-validate signals and accurately identify hands while filtering out other body parts or objects
Solution Approach 2:
The patent employs a multi-functional sensor system where the same sensor array serves multiple detection purposes: hand presence detection, hand position tracking, and hand identification. This universal approach allows a single system to perform multiple functions that would otherwise require separate systems, improving both accuracy and efficiency
Data Source
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AI summary
A computer-implemented method for determining an information on whether at least one hand of a vehicle driver cooperates with a manual steering element of a vehicle, wherein the method comprises: taking at least one image by means of at least one sensor mounted on the vehicle, wherein the at least one image captures at least a manual steering element of the vehicle; and determining, on the basis of the at least one image, an information on whether at least one hand of a vehicle driver cooperates with the manual steering element.