Lane Positioning via Segmented Landmark Alignment
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Solution Overview
Problem
Existing methods for determining the position of a lane using camera-based systems are unreliable in poor weather or heavy traffic conditions, as roadway markings can be obscured, making it difficult to safely establish lane positions.
Innovation Solution
A method and system that utilize specific landmarks, such as street lamps, by recording and evaluating images to segment and align these landmarks into vertical and horizontal components, allowing for the determination of lane position based on their alignment, employing object detection algorithms and neural networks like Convolutional Neural Networks (CNNs) for accurate object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera-based detection of roadway markings is used, then lane position can be determined, but reliability deteriorates in poor weather or heavy traffic conditions
Solution Approach 1:
The patent introduces landmarks (such as street lamps, traffic lights, or other fixed objects) as intermediary reference points to determine lane position. Instead of directly detecting roadway markings that may be obscured, the system uses these intermediary landmarks that are visible even in poor weather or heavy traffic conditions to infer lane positions through geometric relationships and alignment algorithms.
2Measurement precision
If roadway markings are used for lane detection, then lane position can be established, but measurement precision deteriorates when markings are concealed
Solution Approach 1:
The patent segments the detection task into multiple components: detecting landmarks, determining landmark positions and orientations, calculating lane positions based on landmark alignments, and verifying results. This segmentation allows the system to use robust landmark detection while maintaining precise lane position measurement through computational geometry, even when roadway markings are not visible.
3Measurement precision
If landmarks are segmented into multiple segments, then alignment and lane position determination improve, but device complexity increases
Solution Approach 1:
The patent applies segmentation to divide landmarks into multiple segments (e.g., pole body, lamp head, or other distinct parts). By segmenting the landmark and analyzing the alignment and spatial relationships between these segments, the system achieves more accurate lane position determination. The complexity is managed through algorithmic approaches that process these segments systematically.
Solution Approach 2:
The patent transitions from two-dimensional image coordinates to three-dimensional spatial relationships by establishing alignment between segmented landmark parts. This dimensional transformation enables precise lane position calculation while the computational complexity is managed through efficient geometric algorithms that operate on the transformed coordinate system.
Data Source
AI summary
A method for determining a position of at least one lane is disclosed The method includes the following: recording at least one image of the surroundings of an ego vehicle by means of a camera of the ego vehicle; evaluating the image of the surroundings by means of an evaluation device; establishing at least one landmark in the image of the surroundings; segmenting the at least one landmark into at least two segments; establishing the alignment of the at least two segments of the at least one landmark; establishing the position of the at least one lane based on the established alignment of at least one of the at least two segments.