Vehicle Free-Space Boundary Navigation From Road-Edge Camera Images
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately navigating road segments due to the need to process and interpret visual information from cameras, including detecting objects on road edges and dynamic elements like pedestrians and vehicles, while ensuring safe navigation.
Innovation Solution
The system employs multiple cameras to capture images, analyze them to determine a free space boundary relative to objects on the road segment, and use this information to guide navigational actions, utilizing processors and memory units to execute navigational responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the autonomous vehicle uses camera-based visual information processing to detect objects and navigate, then the system can operate without complex sensor arrays, but the accuracy of detecting objects on road edges and determining free space boundaries deteriorates
Solution Approach 1:
The patent transforms 2D camera images into 3D spatial understanding by detecting vanishing points and constructing vanishing line representations. This dimensional transformation allows the system to infer depth, distance, and spatial relationships from planar image data, enabling accurate free space boundary determination without additional 3D sensors.
Solution Approach 2:
The system changes the parameter representation from raw pixel coordinates to geometric features (vanishing points, vanishing lines, and their intersections). By transforming image parameters into meaningful geometric constructs, the system extracts accurate spatial information about road edges and free space boundaries from standard camera images.
2Reliability
If the vehicle system processes detailed visual information to accurately identify safe navigation areas, then navigation safety improves, but the computational processing time increases
Solution Approach 1:
The patent extracts only the essential geometric features (vanishing points and vanishing lines) from complex images, discarding redundant pixel-level details. This selective extraction of critical spatial information maintains navigation safety by focusing computation on the most important boundary-defining features while significantly reducing processing requirements.
Solution Approach 2:
The system performs preliminary geometric analysis by detecting vanishing points and constructing vanishing lines before determining free space boundaries. This preliminary structuring of spatial information creates a simplified geometric framework that accelerates subsequent navigation decisions compared to processing raw pixel data.
3Device complexity
If the autonomous vehicle relies on extracted visual data to make real-time navigation decisions, then the system can operate with fewer sensors, but the ability to accurately derive 3D position and velocity information deteriorates
Solution Approach 1:
The patent recovers 3D spatial information by analyzing the geometric relationships of vanishing points and vanishing lines in 2D images. The intersection points of vanishing lines provide depth cues that enable the system to infer 3D positions of road features and objects, compensating for the lack of dedicated 3D sensors through mathematical reconstruction.
Data Source
AI summary
A system for navigating a host vehicle relative to a road segment may comprise at least one processor comprising circuitry and a memory. the memory may include instructions that when executed by the circuitry cause the at least one processor to: receive at least one image captured by at least one camera from an environment of the host vehicle, wherein the at least one image includes representations of at least two objects with offset edges in the environment of the host vehicle and located on one side of the road segment; analyze the at least one image to determine a free space boundary relative to the at least two objects, wherein the free space boundary represents an edge of at least one region of free space and follows a path different from a path represented by the offset edges of the at least two objects; determine at least one navigational action based on the free space boundary; and cause the host vehicle to implement the at least one navigational action.