Driver Wakefulness Gesture Detection for Vehicle Mode Switching
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Solution Overview
Problem
The transition from automatic driving to manual driving in vehicles often results in safety issues due to inadequate detection of driver wakefulness, leading to potential traffic jams and accidents, especially in high-traffic areas without designated evacuation zones.
Innovation Solution
A vehicle control system that images the driver, detects gesture actions indicating wakefulness, and switches driving modes accordingly, utilizing a combination of imaging devices, biological sensors, and machine learning to accurately determine the driver's state and ensure safe takeover.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If emergency stopping is performed when takeover to manual driving is not successfully performed, then driver safety is improved, but traffic congestion occurs in high-traffic areas
Solution Approach 1:
The system performs preliminary detection of driver wakefulness using gesture recognition before completing the takeover process. By detecting gestures indicating wakefulness (such as head movements, hand movements) in advance, the system can determine driver readiness before emergency stopping is triggered, thereby avoiding unnecessary emergency stops and resulting traffic congestion while maintaining driver safety
Solution Approach 2:
The patent replaces the mechanical emergency stopping mechanism with an optical detection system (imaging device) that uses machine learning to recognize gestures. This substitution allows for earlier intervention and more nuanced assessment of driver state, enabling the system to differentiate between genuine unresponsiveness and temporary distractions, thus reducing false emergency stops and associated traffic congestion
2Measurement precision
If driver wakefulness detection is enhanced using imaging devices and gesture recognition, then accuracy of driver state assessment is improved, but device complexity increases
Solution Approach 1:
The imaging device is designed to perform multiple functions: capturing driver images, detecting gestures indicating wakefulness, and providing visual feedback to the driver. By making the imaging device multi-functional, the system achieves improved driver state detection accuracy without proportionally increasing overall system complexity, as the same hardware component serves multiple purposes
Solution Approach 2:
The system uses machine learning models that have been trained on gesture data to create a digital representation of wakeful gestures. This copying approach allows the system to recognize complex driver states with high accuracy while keeping the real-time processing requirements manageable, as the complex pattern recognition has been pre-computed and stored in the learning model
Data Source
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AI summary
There is provided a vehicle control device including an imager that images a driver, and circuitry configured to detect a gesture action indicating that the driver is awake based on an image captured by the imager, and switch a driving mode in response to the detected gesture action.