Road Surface Brightness Detection for Vehicle Light Source Recognition
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Solution Overview
Problem
Conventional techniques for detecting surrounding vehicles using light sources struggle when light reflected from the road surface is not detectable, leading to inaccurate vehicle light source recognition and control in various traveling environments.
Innovation Solution
A traveling environment detection device that captures images and extracts parameters related to road surface brightness, using this information to estimate the environment and determine the presence of vehicle light sources based on probability, thereby improving detection accuracy and controlling headlight settings to prevent dazzling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If brightness of the whole captured image or midair is used for detection, then detection coverage is improved, but detection accuracy deteriorates due to influence from specific light sources
Solution Approach 1:
The patent segments the captured image into multiple regions including road surface regions, sky regions, and other areas. By specifically selecting road surface regions for brightness parameter extraction, the system isolates the relevant detection area from distracting elements like headlights or taillights, thereby maintaining detection coverage while improving brightness measurement accuracy.
2Reliability
If light source detection is performed in all traveling environments, then vehicle recognition capability is improved, but false positive rate increases in environments without detectable road surface reflection
Solution Approach 1:
The system dynamically adjusts its detection strategy based on the detected traveling environment. When the environment is classified as suitable for road surface reflection detection, the system uses brightness parameter extraction from road surfaces. When the environment is unsuitable (e.g., tunnel, overpass), the system switches to alternative detection methods, thereby maintaining reliable vehicle recognition while minimizing false positives across varying conditions.
Solution Approach 2:
The patent changes the detection parameters based on the traveling environment type. In environments with detectable road surface reflection, the system uses brightness parameters extracted from road surfaces. In environments where road surface reflection is not detectable, the system transitions to using other parameters such as light source position, intensity, or pattern recognition, thereby adapting to different conditions and reducing false positives.
3Productivity
If probability information is fixed for light source determination, then processing speed is improved, but determination accuracy deteriorates in varying traveling environments
Solution Approach 1:
The system implements dynamic probability information that changes based on the detected traveling environment. When a new environment type is detected, the system updates the probability thresholds and criteria for light source determination. This dynamic adjustment maintains processing speed by using pre-defined environment-specific parameters while improving determination accuracy by adapting to the current traveling conditions.
Data Source
AI summary
A driving environment detection device acquires a captured image of the direction the host vehicle is travelling in, and from the captured image, extracts parameters relating to brightness of a road surface for a road driven by the host vehicle. Then, on the basis of the parameters, the driving environment of the vehicle is estimated. By way of such a light control system, it is possible to more accurately detect ambient brightness by estimating the driving environment in accordance with the parameters related to the brightness of the road surface. Therefore, it is possible to accurately detect the driving environment.