Vehicle Headlamp Beam Control via Dynamic Threshold Extraction
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Solution Overview
Problem
Current vehicle exterior environment recognition systems face challenges in accurately identifying tail lamps of preceding vehicles, leading to potential irradiation with high beams, which can cause glare and safety issues.
Innovation Solution
A vehicle exterior environment recognition apparatus that includes a preceding vehicle extractor, a recognizer, and a light-distribution controller, which extracts tail lamps from images, recognizes preceding vehicles, and switches between low and high beams based on the recognition results to prevent irradiation, using a threshold-based approach for accurate identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a threshold-based approach is used to extract tail lamps from images, then the identification accuracy of tail lamps is improved, but the system may still incorrectly identify non-tail lamp regions as tail lamps leading to high beam irradiation
Solution Approach 1:
The system acquires result information about actual beam application from the illumination mechanism and feeds it back to the tail lamp extraction process. The extraction threshold is dynamically adjusted based on whether low beam or high beam is actually applied, allowing the system to learn from past decisions and improve identification accuracy while preventing harmful high beam irradiation of preceding vehicles
Solution Approach 2:
The extraction threshold parameter is changed dynamically based on beam application status. When low beam is applied, a first threshold is used; when high beam is applied, a second (different) threshold is used. This parameter adaptation allows the system to optimize tail lamp identification accuracy under different operating conditions and prevent misidentification that would lead to harmful high beam irradiation
2Measurement precision
If the extraction threshold is set to improve tail lamp identification accuracy, then fewer false positives occur, but the system complexity increases due to dynamic threshold adjustment
Solution Approach 1:
The system performs self-adjustment of the extraction threshold based on its own operational state (beam application status). The light-distribution controller automatically modifies the threshold parameter according to whether low or high beam is applied, without requiring external intervention or complex manual calibration, thereby improving identification accuracy while keeping the adjustment mechanism relatively simple
Data Source
AI summary
A vehicle exterior environment recognition apparatus includes a computer and an illumination mechanism. The computer serves as a preceding vehicle extractor that extracts a tail lamp of a preceding vehicle, a preceding vehicle recognizer that recognizes the preceding vehicle on a basis of the extracted tail lamp, and a light-distribution controller that determines a light distribution of a headlamp. The illumination mechanism switches between a low beam and a high beam on a basis of instruction issued by the light-distribution controller. The preceding vehicle extractor acquires instruction information related to the instruction on the determination issued by the light-distribution controller and result information related to a result of beam application performed by the illumination mechanism, and extracts, by a threshold corresponding to the low beam, the tail lamp for a region in which either one of the instruction information and the result information indicates application of the low beam.