Driver Gaze and Object Tracking for Reliable ADAS Triggering
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Solution Overview
Problem
Existing driver assistance systems struggle to accurately determine driver awareness, leading to false positives or negatives in triggering safety measures like automatic emergency braking, due to limitations in monitoring techniques that rely solely on driver input.
Innovation Solution
A method that combines object tracking around the vehicle with gaze direction analysis to determine the driver's field of view, allowing for accurate detection of objects within or outside the driver's view and adjusting safety measures accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If driver awareness is determined solely based on driver input signals, then the monitoring system is simple to implement, but the accuracy of driver awareness determination deteriorates leading to false positives and negatives
Solution Approach 1:
The patent combines multiple monitoring approaches: traditional driver input signal monitoring with new gaze direction tracking and object detection systems. By merging these different data sources, the system achieves more accurate driver awareness determination while distributing the complexity across multiple specialized subsystems rather than one complex monolithic system.
Solution Approach 2:
The patent introduces an intermediary processing layer that correlates gaze direction data with object detection data to determine whether the driver is aware of specific objects. This intermediary analysis layer bridges the gap between raw sensor data and driver awareness assessment, improving accuracy without requiring direct complex integration of all sensors.
2Reliability
If safety systems are triggered based on limited driver input monitoring, then the system responds quickly, but false triggers increase reducing system reliability
Solution Approach 1:
The system performs preliminary correlation analysis between gaze direction and object detection data before triggering safety measures. By pre-processing and correlating this information in advance, the system builds a more reliable awareness assessment that reduces false positives, while still maintaining quick response capability when genuine dangers are detected.
Solution Approach 2:
The system uses feedback from multiple data sources (gaze tracking, object detection, driver input) to continuously refine its assessment of driver awareness. This multi-source feedback mechanism improves reliability by cross-validating information before triggering safety systems, reducing false positives while maintaining appropriate response times.
3Loss of information
If the system monitors only driver input signals, then the data processing requirement is low, but the ability to detect false awareness deteriorates
Solution Approach 1:
The patent segments the monitoring system into specialized subsystems: gaze tracking module, object detection module, and correlation analysis module. Each segment processes specific types of data independently, reducing the computational burden on any single processor while collectively providing comprehensive driver awareness information that reduces false positives.
Data Source
AI summary
A computer-implemented method for assisting a driver of a vehicle includes determining, based on a gaze direction of the driver, a field of view of the driver. The method includes detecting, using an object tracking system, that one or more objects are present around the vehicle. The method includes determining that one or more of the detected objects are outside of the field of view of the driver. The method includes performing an action in response to it being determined that one or more objects are outside of the field of view of the driver.