Lane Information Display Using Distance-Segmented Curve Fitting
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Solution Overview
Problem
Current lane departure warning systems are limited in accuracy due to reliance on electronic maps, which can differ from actual driving conditions, and struggle with curved sections and long distances, leading to reduced effectiveness in providing reliable lane recognition and guidance.
Innovation Solution
An electronic device that acquires images while driving, divides them based on distance, detects lane lines, curve-fits them to continuous curves, and displays the results on a user interface, using vanishing points and front vehicles as reference points to enhance lane recognition and guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If lane recognition is based on electronic map information, then the system can provide route guidance, but the accuracy of lane recognition deteriorates due to differences between actual driving lanes and map information
Solution Approach 1:
The patent replaces electronic map-based lane recognition with a vision-based detection system using cameras and image processing algorithms. The system captures images of road lane markings and uses computer vision techniques to detect and track lane positions, substituting the mechanical/electronic map system with an optical sensing and processing system that directly observes actual lane positions.
Solution Approach 2:
The patent introduces an intermediary image processing system that acts as a mediator between the camera sensor and the lane recognition output. This intermediary layer includes algorithms for detecting lane markings, filtering noise, and reconstructing lane paths, which bridges the gap between raw visual data and accurate lane position information.
2Device complexity
If lane recognition operates only at short distances and straight lines, then the system can maintain simple processing, but the applicability of lane departure warning deteriorates for curved sections and long distances
Solution Approach 1:
The patent implements dynamic lane recognition that adapts to different road geometries. The system adjusts its detection parameters and algorithms based on whether the road is straight or curved, allowing it to handle both simple and complex scenarios. The lane tracking system dynamically updates lane positions and curvature estimates to maintain accuracy across varying conditions.
Solution Approach 2:
The patent divides the road ahead into multiple detection zones or segments at different distances. By segmenting the detection area, the system can apply different processing strategies to near and far regions, improving both processing efficiency and accuracy for long-distance curved road detection.
3Device complexity
If lane recognition is performed only when no car is in front of the driving lane, then processing is simplified, but the reliability of lane departure warning deteriorates in real traffic conditions
Solution Approach 1:
The patent performs preliminary detection of lane markings and lane positions in advance, before needing to make lane departure decisions. By continuously pre-processing and tracking lane information ahead of time, the system maintains ready-to-use lane position data even when vehicles are present, improving response reliability without proportional increases in processing complexity.
Data Source
AI summary
The present disclosure relates to a method for displaying lane information of an electronic device. The method for displaying lane information according to the present disclosure includes: acquiring an image photographed while a vehicle is driving; dividing the acquired image according to a distance from the vehicle; detecting lane display lines in the divided areas; curve-fitting the detected lane display lines to a continuous curve; and displaying the curve-fitted curve on a predetermined user interface. According to the present disclosure, it is possible to improve the route visibility to the driver by recognizing the far-distance lane by determining whether the vehicle is in the driving lane. In addition, it is possible to more accurately provide the route guidance information by using the real-time lane recognition results for the display of the route guidance.