Rear Camera Lane Estimation via Distortion Correction
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Solution Overview
Problem
Current navigation systems fail to provide users with the ability to automatically determine their vehicle's lane position during various road conditions, which is essential for operator awareness and safe navigation.
Innovation Solution
A navigation system that uses a rear-facing camera to generate images of the roadway, applies distortion adjustments, identifies lane pixels based on correlation with lane markings, and calculates the vehicle's lane position through a road lane model estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a rear-facing camera is used to capture roadway images for lane position determination, then operator awareness and safety are enhanced through real-time lane information, but device complexity increases due to the need for image processing, distortion correction, and lane detection algorithms
Solution Approach 1:
The patent uses an intermediary processing system that includes a communication unit to receive camera images, a control unit to process the images through distortion correction and lane pixel identification, and generates a road lane model. This intermediary system acts as a mediator between the simple camera input and the complex lane position determination output, breaking down the complexity into manageable processing stages while maintaining high reliability in lane position accuracy.
2Measurement precision
If distortion adjustment is applied to rear-facing camera images to improve lane marking correlation, then measurement precision of lane position is improved, but processing time and computational requirements increase
Solution Approach 1:
The patent applies preliminary distortion adjustment to the rear-facing camera images before performing lane pixel identification and road lane model generation. By pre-correcting the distortion in the captured images, the system prepares the data in advance for more efficient and accurate lane marking correlation, reducing the computational burden during real-time processing and minimizing processing time while maintaining high measurement precision.
Data Source
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AI summary
A navigation system (100) includes: generating a rear facing camera image (450) representing a field of view (232) of the rear facing camera (230) including a current roadway (206) on which the user vehicle (212) is traveling; generating a distortion adjustment rear facing image (462) based on the rear facing camera image (450); identifying lane pixels (466) based on correlation of image pixels (452) of the distortion adjustment rear facing image (462) to lane markings of the current roadway (206); generating a road lane model (202) including a lane delineation estimation (204) based on the lane pixels (466); and calculating a lane position (208) for the user vehicle (212) according to the lane delineation estimation (204).