Vehicle Environment Classification via Brightness Analysis
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Solution Overview
Problem
Existing vehicle systems lack reliable proactive detection of future vehicle environments, which is essential for anticipatory control of lighting and window/sunroof operations, particularly when entering tunnels or similar environments, as they rely on reactive rather than predictive methods.
Innovation Solution
A camera system that processes a sequence of images to determine brightness changes in specific image sections, allowing for the inference of the vehicle environment, and uses this information to control functional units like lighting and window control, by comparing brightness in central and peripheral image sections to identify approaching features like tunnel entrances or forest areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera system is aligned to detect the lane course centrally, then lane detection is optimized, but the ability to detect dark objects like tunnel entrances at a distance is reduced because they appear larger and darker in the center image section
Solution Approach 1:
The image is divided into multiple evaluation regions (first image section in the center, second image section in the upper edge area). By segmenting the image into different zones with different evaluation purposes, the system can simultaneously optimize for lane detection in the center while detecting tunnel entrances in the upper edge region, resolving the contradiction between these two detection tasks.
2Loss of time
If the vehicle enters a dark area suddenly, then immediate light switching is required, but reactive control does not allow timely closing of windows or optimal preparation
Solution Approach 1:
The system performs preliminary detection of dark areas using the camera system before the vehicle actually enters them. By evaluating brightness in the first and second image sections and comparing the brightness ratio, the system can predict upcoming dark areas and trigger anticipatory control actions (light switching, window closing) in advance, transforming reactive control into proactive control and eliminating the time loss associated with sudden environmental changes.
3Device complexity
If conventional camera systems are used for lane detection and traffic sign detection, then existing infrastructure is utilized, but they cannot reliably detect future vehicle environments for anticipatory control
Solution Approach 1:
The patent makes the existing camera system universal by enabling it to perform multiple functions: traditional lane detection, traffic sign detection, and the new function of detecting future vehicle environments for anticipatory control. This is achieved by adding the brightness evaluation method that compares first and second image sections, allowing the same camera hardware to serve multiple purposes without increasing device complexity while significantly enhancing adaptability.
Data Source
AI summary
The invention specifies a method for a motor vehicle for predictive classification of a future vehicle environment and the light conditions thereof. To this end, a camera system is oriented with respect to a region ahead of the vehicle. A sequence of images is recorded. In a prescribed central image detail, the change of brightness per unit of time and/or distance is determined and this is used to infer the environment ahead of the vehicle.