Blind-Spot Monitoring Using Driver Eye Tracking and Camera Vision
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Solution Overview
Problem
Current blind-spot detection systems in vehicles are expensive and rely on assumptions about typical blind spots, failing to account for individual driver's actual field of view, leading to ineffective warnings and potential accidents.
Innovation Solution
A camera and sensor system that determines a driver's field of view and location of objects within their blind spots using machine vision, generating precise warnings based on actual visibility, rather than relying on pre-determined zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar-based blind-spot detection systems are used, then detection capability is improved, but system cost increases
Solution Approach 1:
The patent uses camera-based vision systems to create a visual copy or representation of the blind spot area, replacing expensive radar hardware with more affordable camera technology while maintaining detection functionality through image processing algorithms
Solution Approach 2:
The patent substitutes mechanical/radar-based detection systems with optical camera-based systems, replacing physical wave transmission and reception with light-based imaging and computer vision processing to reduce cost while preserving detection capability
2Device complexity
If pre-determined blind spot zones are used for warnings, then system simplicity is improved, but accuracy of blind spot identification deteriorates
Solution Approach 1:
The patent dynamically adjusts blind spot boundaries based on real-time detection of actual vehicles or objects in the environment, rather than using fixed pre-determined zones, allowing the monitoring areas to adapt and move according to traffic conditions and driver position
Solution Approach 2:
The system uses feedback from camera imaging and object detection to continuously refine and update blind spot boundaries, comparing detected objects against dynamic monitoring zones to accurately determine whether vehicles are truly in blind spots rather than relying on static assumptions
3Loss of time
If warnings are provided based on assumed blind spots, then response time is improved, but warning effectiveness deteriorates
Solution Approach 1:
The system performs preliminary detection and classification of objects in potential blind spot areas using camera imaging before issuing warnings, allowing advance identification of actual vehicles versus other objects to ensure warnings are only triggered when truly necessary
Data Source
AI summary
An apparatus includes a camera, a sensor and a processor. The camera may generate a video signal based on a targeted view of a driver. The sensor may generate a proximity signal in response to detecting an object within a predetermined radius. The processor may determine a location of the object with respect to the vehicle, determine a current location of eyes of the driver, determine a field of view of the driver at a time when the proximity signal is received based on the current location of the eyes, determine whether the object is within the field of view using the current location of the eyes, and generate a control signal. The distance may be determined based on a comparison of reference pixels of a vehicle component in a reference video frame to current pixels of the vehicle component in the video frames.