Lane Departure Warning System Using Multi-Sensor Fusion
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Solution Overview
Problem
Existing lane departure warning systems are prone to erroneous judgments due to weather conditions, such as rain, which affect image quality and accuracy in detecting unintended lane departures.
Innovation Solution
The system employs multiple image acquisition units, including both conventional and infrared cameras, with environment evaluation modules to assess brightness and weather status, allowing for selective use of image sources to enhance detection accuracy and issue alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing techniques are used for lane departure detection, then the system structure remains simple, but detection accuracy deteriorates under adverse weather conditions such as rain and night
Solution Approach 1:
The patent segments the image acquisition function into multiple specialized units: a first image acquisition unit for normal conditions, a second image acquisition unit (infrared camera) for adverse weather conditions, and a third image acquisition unit (millimeter-wave radar) for further enhanced detection. This segmentation allows each unit to specialize in specific detection scenarios, improving overall accuracy under varying weather conditions.
Solution Approach 2:
The patent changes the detection parameter from visible light images to infrared radiation detection when weather conditions deteriorate. The environment evaluation unit assesses weather conditions and switches between different detection modes, utilizing infrared radiation characteristics that are less affected by rain, fog, and darkness, thereby maintaining detection accuracy under adverse conditions.
2Reliability
If multiple image acquisition units are deployed to improve detection accuracy, then detection reliability improves, but device complexity increases
Solution Approach 1:
The patent implements a dynamic system where the environment evaluation unit continuously monitors weather conditions and dynamically selects or combines appropriate detection units. The system transitions from static single-unit detection to dynamic multi-unit coordination based on real-time environmental assessment, improving reliability without requiring all units to operate simultaneously.
Solution Approach 2:
The environment evaluation unit serves as an intermediary that coordinates between multiple image acquisition units and the lane departure determination unit. It assesses weather conditions and directs appropriate detection units, managing system complexity by providing a centralized control layer that simplifies the interaction between multiple components.
3Measurement precision
If environment evaluation is performed to select appropriate image sources, then detection accuracy under varying conditions improves, but processing time and computational load increase
Solution Approach 1:
The environment evaluation unit performs preliminary assessment of weather conditions to determine the appropriate detection mode before actual lane departure detection begins. By pre-evaluating environmental factors such as rain, fog, and darkness, the system prepares the optimal detection configuration in advance, reducing processing time during critical detection phases.
Solution Approach 2:
The system performs environment evaluation periodically rather than continuously, switching between evaluation and detection modes. This periodic action reduces computational load while maintaining detection accuracy, as the environment typically does not change rapidly enough to require constant re-evaluation.
Data Source
AI summary
The present invention discloses a lane departure warning method, which functions to choose the data acquiring source according to brightness of the environment surrounding a vehicle and weather status so as to reduce the erroneous judgment of lane departure during image processing and analyzing. In addition, the present invention also presents a lane departure warning apparatus using the foregoing method, which comprises at least a first information acquisition unit, at least a second information acquisition and a information processing/information processing/controlling unit. The first information acquisition unit disposed on the vehicle is capable of capturing the image around the vehicle while the second information acquisition unit disposed on the bottom of the vehicle is capable of capturing image under the bottom of the vehicle. The image acquired from the first information acquisition unit and the second information acquisition unit is then sent to the processing and information processing/controlling unit for data processing.