Snow Detection via Subsurface Light Scattering Analysis
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Solution Overview
Problem
Current vehicle systems rely on detecting wheel slip or introducing excitations to determine if snow is present on the road, which can be delayed and prone to false detections due to ambient lighting conditions, especially on white-colored surfaces like salt-corrupted dry roads.
Innovation Solution
A vision-based imaging system using a concentrated lighting source, such as a laser LED, that analyzes subsurface scattering of light to differentiate between snow-covered and non-snow-covered surfaces by converting RGB images to Lab space and applying filters like Laplacian of Gaussian or binary conversion, allowing for real-time snow detection without vehicle excitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wheel slip detection or vehicle excitation methods are used to detect snow, then snow detection can be achieved, but detection is delayed and requires vehicle excitations or specific driving conditions
Solution Approach 1:
The system performs preliminary snow detection by analyzing light scattering properties of the road surface before the vehicle encounters snow conditions. The imaging device captures images of the road surface and analyzes subsurface scattering characteristics to detect snow presence in advance, eliminating the need to wait for wheel slip or introduce vehicle excitations to detect snow.
2Adaptability or versatility
If ambient light sensing is used for snow detection, then detection can occur under various lighting conditions, but false detections occur on white-colored surfaces like salt-corrupted dry roads
Solution Approach 1:
An active light source is introduced as an intermediary to illuminate the road surface, enabling the imaging device to capture images independent of ambient lighting conditions. The controlled lighting allows the system to detect subsurface scattering properties of snow without being influenced by environmental light variations, thereby eliminating false detections on white surfaces while maintaining adaptability to various lighting environments.
3Measurement precision
If active lighting source is used for snow detection, then detection accuracy is improved and false detections are reduced, but energy consumption increases
Solution Approach 1:
The active light source operates at partial power levels, providing just enough illumination to enable subsurface scattering analysis without excessive energy consumption. The system uses the light source only when snow detection is needed, rather than continuously, and employs efficient LED technology to minimize energy usage while maintaining detection accuracy.
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
This method enables early and accurate detection of snow without driver interventions, reduces false positives on white surfaces, and maintains effectiveness across varying ambient lighting conditions, thereby enhancing vehicle safety and traction control.
Implementation Method 1
A determination is made whether snow is present on the path of travel based on the subsurface scattering of the light
Data Source
AI summary
A method for determining a snow covered surface condition of a path of travel. A beam of light is emitted at a surface of the path of travel by a light emitting source. An image of a path of travel surface is captured by an image capture device. The image capture device is mounted on the vehicle and captures an image in a downward direction. The captured image captures the beam of light emitted on the path of travel surface. Analyzing a subsurface scattering of the light generated on the path of travel surface by a processor. A determination is made whether snow is present on the path of travel. A snow covered path of travel surface signal is generated in response to the identification of snow on the path of travel.