Lane Detection via Road Edge Corridor Analysis
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Solution Overview
Problem
Current driver assistance systems struggle to detect lanes reliably in the absence of or with incomplete lane markings, which limits their effectiveness on roads without clear markings, such as country roads.
Innovation Solution
A method involving image recording, corridor detection, and structure detection using camera data, combined with vehicle dynamics and environmental sensors, to identify and estimate the lane edge regardless of markings, employing 3D reconstruction and pattern recognition techniques to enhance detection accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lane detection relies on traditional lane markings, then detection accuracy is improved, but reliability deteriorates on roads without clear markings
Solution Approach 1:
The patent introduces road edge detection as an intermediary element to bridge the gap between traditional lane marking detection and reliable lane identification. By detecting the road edge through corridor detection and structure detection, the system can infer lane position even when lane markings are absent or incomplete, thus maintaining reliability across different road conditions while preserving detection accuracy through the relationship between road edge and lane position
Solution Approach 2:
The system achieves universality by making the lane detection system functional both with and without lane markings. The method uses camera data combined with vehicle dynamics and environmental sensors to detect road edges universally, then applies pattern recognition to identify lanes regardless of marking presence. This multi-functional approach ensures the system works reliably on highways with clear markings and on country roads without markings
2Measurement precision
If lane detection is limited to marked roads, then detection precision is improved, but adaptability deteriorates to roads without markings
Solution Approach 1:
The system applies dynamics by adaptively switching detection strategies based on environmental conditions. The method uses vehicle dynamics data (speed, steering angle, acceleration) to adjust the detection approach - relying more on pattern recognition of lane markings when conditions are favorable, and transitioning to road edge-based corridor detection when markings are absent. This dynamic adaptation maintains precision across varying road conditions
Solution Approach 2:
The system changes detection parameters based on the presence or absence of lane markings. When markings are detected, the system uses their position and characteristics for lane identification. When markings are absent, it transitions to using road edge position, corridor geometry, and environmental features as detection parameters. This parameter transformation enables the system to adapt to different road types while maintaining detection precision
3Reliability
If multiple sensors and processing techniques are combined, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the lane detection system into distinct functional modules: camera data acquisition, vehicle dynamics data acquisition, environmental sensor data acquisition, corridor detection, structure detection, pattern recognition, and data fusion. Each module performs a specific function and processes data independently before combining results. This segmentation improves reliability through modular redundancy while managing complexity by organizing functions into separate, manageable units with defined interfaces
Data Source
AI summary
The invention relates to a method for detecting a lane having the steps: - taking at least one image of the surroundings of a vehicle with a camera, - detecting a driving corridor from the at least one image and - structure detection by taking into account the identified driving corridor, in order to determine an image of the profile of at least one roadway edge from the at least one image.