Vanishing Point Detection for Autonomous Vehicle Lane Calibration
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Solution Overview
Problem
Determining vanishing points in images for autonomous driving vehicles is challenging due to the difficulty in accurately identifying and indicating these points, which affects the calibration of sensors and the accuracy of neural networks used for motion planning and control.
Innovation Solution
A method involving neural networks that analyze images to determine vanishing points by identifying line segments and calculating their intersections, with the vanishing point represented as a relative distance to the image center, allowing for more precise calibration of sensors and improved motion planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine vanishing points by manual identification, then the process is simple to understand, but the accuracy and precision of vanishing point determination is poor
Solution Approach 1:
The patent replaces manual mechanical identification of vanishing points with an automated computational system using neural networks and image processing algorithms. The system automatically detects lane lines, calculates their intersections, and determines vanishing points without human intervention, thereby improving precision while managing complexity through algorithmic automation.
Solution Approach 2:
The patent introduces intermediate processing steps including lane line detection, line segment extraction, and intersection calculation as mediators between the input image and the final vanishing point determination. These intermediary processes break down the complex task into manageable stages, each contributing to the overall accuracy while maintaining system organization.
2Reliability
If complex neural network processing is used to determine vanishing points, then the accuracy of sensor calibration is improved, but the processing time and computational complexity increases
Solution Approach 1:
The patent performs preliminary processing by detecting lane lines and extracting line segments before calculating vanishing points. By pre-identifying relevant features and filtering out unnecessary information, the system reduces the computational burden of subsequent vanishing point calculations, thereby decreasing processing time while maintaining calibration accuracy.
Solution Approach 2:
The patent extracts only the essential elements (lane lines and their intersections) needed for vanishing point determination from the complete image data. This extraction process removes redundant information and focuses computational resources on critical features, reducing processing time while preserving the accuracy required for reliable sensor calibration.
Data Source
AI summary
In some implementations, a method is provided. The method includes obtaining an image depicting an environment where an autonomous driving vehicle (ADV) may be located. The image comprises a plurality of line indicators. The plurality of line indicators represent one or more lanes in the environment. The image is part of training data for a neural network. The method also includes determining a plurality of line segments based on the plurality of line indicators. The method further includes determining a vanishing point within the image based on the plurality of line segments. The method further includes updating one or more of the image or metadata associated with the image to indicate a location of the vanishing point within the image.