Driver Monitoring Gaze Prediction Using Virtual Focus Points
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Solution Overview
Problem
Current Driver Monitoring Systems (DMS) fail to effectively address unusual driver conditions such as visual impairments and overlook the relationship between driver gaze and the external environment, leading to inaccurate attention assessment in complex driving scenarios.
Innovation Solution
A dual-sensor system integrating interior and exterior sensors with a computing unit that analyzes data from both to derive a driver's gaze vector by assigning a virtual focus point based on perceived changes, using autocalibration and machine learning to refine gaze predictions, and adapt to individual driver conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single interior camera is used to monitor driver behavior, then the system cost is reduced and device complexity is lowered, but measurement precision of driver attention and gaze accuracy deteriorates
Solution Approach 1:
The patent combines interior camera data with exterior camera data to estimate the driver's gaze vector. By merging information from both interior and exterior sensors, the system achieves more accurate gaze prediction than would be possible with a single interior camera alone, while avoiding the complexity of multiple interior cameras.
Solution Approach 2:
The patent introduces virtual focus points as an intermediary element to bridge interior and exterior sensor data. These virtual focus points represent locations in the external environment that the driver is likely looking at, based on head pose and environmental features, enabling accurate gaze estimation without direct eye tracking.
2Device complexity
If traditional DMS focuses only on interior monitoring, then device complexity is reduced, but adaptability to diverse driver conditions and external interactions deteriorates
Solution Approach 1:
The patent makes the DMS system universal by integrating both interior and exterior monitoring capabilities. The system can handle diverse driver conditions (drowsiness, distraction, visual impairments) and external interactions (road signs, traffic signals, pedestrians) through a unified approach that combines data from multiple sensor types, enhancing overall adaptability.
3Measurement precision
If DMS overlooks the relationship between driver gaze and external environment, then measurement precision of internal states is maintained, but reliability of attention assessment in complex driving scenarios deteriorates
Solution Approach 1:
The patent implements feedback by continuously comparing the estimated gaze vector with actual driver behavior and environmental context. The system uses exterior camera data to identify relevant environmental features and feedback loops to refine gaze predictions, improving the reliability of attention assessment in dynamic driving scenarios.
Data Source
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AI summary
The present disclosure relates to a Driver Monitoring System (DMS) for a vehicle, comprising at least one interior sensor configured to monitor an interior of the vehicle, at least one exterior sensor configured to monitor an environment of the vehicle, and a computing unit, wherein the computing unit is configured to retrieve, analyze and process sensor data from the interior sensor and the exterior sensor; identify a change of the perception in the sensor data from the interior sensor and/or the exterior sensor, wherein the change of the perception is within the field of view of an occupant of the vehicle; assign a virtual focus point to the identified change of the perception; and derive a prediction of the occupant's gaze vector based on the virtual focus point.