Vehicle Fog Detection Using Light Halo Analysis

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Solution Overview

Problem

Existing systems for controlling exterior vehicle lights struggle to reliably detect fog conditions without being in a high beam state, as they often rely on backscatter detection, which may be inhibited in well-lit areas or high traffic situations, leading to potential glare and reduced driver visibility.

Innovation Solution

An imaging system that uses an imager and controller to analyze image data from a low beam state, distinguishing between foggy and clear light sources by detecting light halos and applying light metrics, allowing for fog detection and adjustment of exterior lights without relying on high beams.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If backscatter detection is used to detect fog conditions, then fog detection capability is improved, but reliability deteriorates in well-lit areas or high traffic situations where backscatter may be inhibited

Engineering Contradiction:

Improvefog detection reliabilityVSAvoiddetection capability across different lighting conditions

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system changes the detection parameter from relying on backscatter intensity to analyzing light halo characteristics around light sources. By detecting the presence, size, and intensity distribution of halos around known light sources (headlights, streetlights), the system achieves reliable fog detection across various lighting conditions including well-lit areas and high traffic situations where backscatter may be inhibited.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system uses light sources in the scene as intermediaries to detect fog conditions. Instead of directly measuring backscatter from the vehicle's own lights, the system analyzes how fog affects light from external sources by detecting halos around these light sources. This intermediary approach provides more reliable detection across different environmental conditions.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If high beams are used to enable backscatter detection, then fog detection is possible, but driver visibility and safety deteriorate due to glare

Engineering Contradiction:

Improvefog detection capabilityVSAvoiddriver glare and visibility reduction

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system uses existing light sources in the environment (oncoming vehicle headlights, streetlights, other vehicle lights) to detect fog conditions. Instead of requiring the vehicle's own high beams to create backscatter, the system analyzes halos around these external light sources, making the detection system self-sufficient without needing to activate potentially harmful high beams.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system converts the harmful effect of light scattering in fog (which causes halos and reduces visibility) into a beneficial detection mechanism. By detecting the presence and characteristics of halos around light sources, the system transforms the visual interference caused by fog into a reliable indicator of fog conditions, enabling detection without needing to activate high beams that would worsen driver visibility.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Adaptability or versatility

If light halo detection is used instead of backscatter detection, then adaptability to different lighting conditions is improved, but device complexity increases due to additional image analysis requirements

Engineering Contradiction:

Improvedetection capability in various lighting conditionsVSAvoidimage data analysis complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system applies local quality analysis by focusing image processing specifically on regions around detected light sources. Instead of analyzing the entire image for backscatter patterns, the system identifies light source locations and then analyzes halo characteristics in localized regions around these sources. This approach reduces overall computational complexity while maintaining high adaptability to different lighting conditions.

Inventive Principle:

Principle #3Local quality

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables reliable fog detection and adjustment of vehicle lights in low beam states, improving driver visibility and reducing glare in various lighting conditions, without the need for high beams, thus enhancing safety and reducing driver distraction.

Implementation Method 1

distinguishing between foggy and clear light sources by detecting light halos

Methodology Applied

Scientific EffectLight scattering: Scattering

Data Source

PatentUS9514373B2Imaging system and method for fog detection

Publication Date: 2016.12.06 HL KLEMOVE CORP

AI summary

An imaging system and method for fog detection are disclosed herein. An imager is configured to image a scene external and forward of a controlled vehicle and to generate image data corresponding to the acquired images. A controller is configured to receive and analyze the image data. When exterior lights of the controlled vehicle are operated in a low beam state, the controller is able to detect light sources of interest in the image data, determine if each light source of interest is a foggy light or a clear light, and generate a first signal if a fog entry condition is satisfied.