Lane Line Shrinkage Tracking for Visual Detection Reliability
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Solution Overview
Problem
The reliability of vehicle visual detection is affected by various environmental factors, such as strong light, wet ground, and incomplete lane lines, leading to potential lane departure and steering wheel random operations, posing safety risks.
Innovation Solution
A method and device for determining the reliability of visual detection by receiving visually detected lane line parameters, comparing historical lane line parameters with current ones to calculate a historical shrinkage degree, and determining if there is an error in visual detection based on this degree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If visual detection is used to detect lane lines, then the system can obtain real-time lane line parameters, but the detection reliability deteriorates under environmental factors such as strong light, wet ground, and incomplete lane lines
Solution Approach 1:
The system pre-calculates and stores historical lane line parameters before visual detection is needed. When detection is performed, these pre-prepared historical data are immediately available for comparison, enabling real-time reliability assessment without adding detection delay
Solution Approach 2:
The system establishes a feedback mechanism where detected lane line parameters are continuously compared with historical parameters. The comparison results feed back into the reliability determination process, allowing the system to adjust and improve detection accuracy based on past performance data under various environmental conditions
2Reliability
If historical lane line parameters are compared with current parameters to calculate shrinkage degree, then detection reliability is improved, but system complexity increases
Solution Approach 1:
The determination process is segmented into distinct functional modules: a receiving apparatus for acquiring lane line parameters, a calculation apparatus for computing shrinkage degree, and a determination apparatus for assessing reliability. This modular segmentation makes the complex system more manageable and easier to implement
Solution Approach 2:
The historical lane line parameters serve as an intermediary element between the current detection system and the reliability assessment. By introducing this intermediate data layer, the system can compare current detections with past performance without directly complexifying the core detection mechanism
3Measurement precision
If environmental factors such as strong light and wet ground are present, then visual detection quality deteriorates, but these factors cannot be controlled or eliminated
Solution Approach 1:
The system converts the harmful effect of environmental factors into a beneficial diagnostic tool. By collecting and analyzing historical detection data under various environmental conditions, the system learns to recognize patterns of detection degradation and compensates for them, effectively turning the presence of environmental factors into an opportunity to improve robustness
Solution Approach 2:
The system prepares historical detection data and reliability thresholds in advance to cushion against the impact of environmental factors. When adverse conditions occur, these pre-prepared references provide a buffer that maintains detection reliability despite the harmful environmental influences
Data Source
AI summary
The disclosure relates to a method for determining reliability of visual detection, the method including: receiving a visually detected lane line parameter; comparing a historical lane line parameter with the received lane line parameter, to calculate a historical shrinkage degree of a lane line; and determining, based on the historical shrinkage degree, whether there is an error in the visual detection. The disclosure further relates to a device for determining reliability of visual detection, a computer storage medium, an autonomous driving system, and a vehicle.