Vehicle Cabin Sunload Mapping Using Camera ROI and Occupant Removal
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Solution Overview
Problem
Existing sunload determination methods in vehicles rely on dedicated ambient light sensors, which provide only a single measurement and are inadequate for accurately determining sunlight levels at multiple locations within the passenger cabin, as image data from cameras does not directly correlate with ambient light and is influenced by object colors and shadows.
Innovation Solution
A camera-based system processes image data from interior and exterior cameras to generate a sunload map by using region-of-interest overlays to extract relevant data, an occupant overlay to account for dynamic occupants, and an ambient light model with environmental parameters to estimate sunload values at multiple locations within the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single ambient light sensor is used to determine sunload, then the device complexity is reduced, but the measurement precision is insufficient for multiple locations in the passenger cabin
Solution Approach 1:
The patent reuses existing cameras that were originally designed for other functions (monitoring, backup views, obstacle detection) and makes them serve a dual purpose by extracting sunload information from their image data. This eliminates the need for dedicated ambient light sensors while providing multi-location sunload measurements across the passenger cabin.
Solution Approach 2:
The patent creates a virtual sunload measurement system by processing image data from cameras to generate a sunload map that represents sunlight distribution across multiple locations. This virtual copying approach replaces physical sensors with computational derivation, achieving precise multi-location measurements without additional hardware.
2Device complexity
If camera image data is used to determine sunload, then the device complexity is reduced, but the measurement precision is affected by object colors and shadows
Solution Approach 1:
The patent applies region-of-interest (ROI) overlays to selectively process only specific regions in the camera images that are relevant for sunload measurement. By focusing on predetermined scene elements and excluding areas with occupants or irrelevant objects, the system maintains measurement accuracy while reducing the impact of confounding factors like object colors and shadows.
Solution Approach 2:
The patent extracts only the necessary image data corresponding to predetermined scene elements using ROI overlays, and removes or excludes data from regions containing vehicle occupants or other interfering elements. This extraction process isolates the relevant sunlight information from confounding factors, maintaining measurement precision while simplifying processing.
3Measurement precision
If multiple dedicated sensors are installed for multi-location sunload measurement, then the measurement precision is improved, but the device complexity and cost increase
Solution Approach 1:
The patent enables existing cameras to perform multiple functions - their original monitoring/detection roles plus sunload measurement across multiple locations. By generating a sunload map from single camera images through computational processing, the system achieves multi-location measurement capability without installing multiple physical sensors, thereby reducing device complexity and cost.
4Ease of manufacture
If existing cameras are used for sunload determination, then the manufacturing precision is improved by reusing components, but the measurement precision is compromised due to lack of direct correlation with ambient light
Solution Approach 1:
The patent transforms camera image data into sunload measurements by applying environmental parameters including sun position information. The mapper generates sunload values by combining processed image intensity data with solar geometry calculations, creating a reliable correlation between camera observations and actual ambient light conditions despite the indirect measurement approach.
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 approach allows for accurate determination of sunload across the vehicle cabin without the need for ambient light sensors, improving the accuracy of HVAC control, display brightness, and other vehicle systems by providing a detailed sunload profile based on camera image data and environmental conditions.
Implementation Method 1
the image data captured by onboard cameras (interior and/or exterior) may depend on reflected solar radiation
Data Source
AI summary
A vehicle characterizes a sunload on the vehicle using an imaging system including at least one camera capturing image data (e.g., without using an ambient light sensor). The image data includes at least a portion of a passenger cabin. A region of interest (ROI) overlay receives the image data and extracts selected image data according to predetermined scene elements of the vehicle environment. An occupant overlay is configured to detect a vehicle occupant represented in the selected image data and configured to generate truncated image data by subtracting image data corresponding to the vehicle occupant from the selected image data. An ambient light model uses environmental parameters including a sun position to estimate an expected sunload range. A mapper generates a sunload map comprising respective sunload values for a plurality of locations on the vehicle according to the truncated image data and the expected sunload range.