Optical Vehicle Movement Sensing for Low-Speed and Yaw Tracking
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Solution Overview
Problem
Conventional vehicle movement tracking systems, such as those using GPS and ABS sensors, face inaccuracies in noisy environments and low-speed scenarios, and struggle to precisely determine longitudinal and yaw movements due to limitations in wheel rotation measurement and reliance on road markings.
Innovation Solution
An optical movement tracking sensor system utilizing an optoelectronic sensor and processor for digital image correlation of sequential pixel pattern images from multiple sample areas on the road surface, allowing accurate tracking of vehicle movement without relying on road features, and adjusting sampling areas based on vehicle speed to enhance accuracy at both low and high speeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS sensor is used for vehicle position tracking, then global position can be determined, but accuracy is lost in noisy environments and shielded areas
Solution Approach 1:
The patent introduces an optical flow sensor as an intermediary measurement device that captures road surface patterns through an optoelectronic sensor. This intermediary system provides position tracking data that complements GPS, maintaining accuracy in environments where GPS fails by measuring the relative movement of pixel patterns from the road surface.
Solution Approach 2:
The patent replaces reliance on satellite-based electromagnetic signals (GPS) with an optical measurement system that directly senses road surface patterns. This substitution uses digital image correlation of pixel patterns to determine vehicle movement, providing a mechanism that works independently of satellite signal availability.
2Speed
If ABS tachometer is used for speed measurement, then high-speed accuracy is achieved, but resolution is too low for low-speed positional determination
Solution Approach 1:
The patent segments the measurement function by using two different sampling areas: a first sample area for low-speed measurement with higher resolution, and a second sample area for high-speed measurement. This segmentation allows the system to optimize measurement precision for each speed regime by selecting the appropriate sampling area.
Solution Approach 2:
The patent dynamically switches between different sampling areas based on vehicle speed. The processor selects the first sample area when the vehicle is moving at low speed to achieve higher positional resolution, and switches to the second sample area at higher speeds, making the measurement system adaptive to operating conditions.
3Device complexity
If single sample area is used for optical flow measurement, then processing is simplified, but accuracy at different speeds cannot be optimized
Solution Approach 1:
The patent implements a dynamic sampling strategy where the processor selectively activates different sample areas based on detected vehicle speed. This dynamic approach optimizes measurement precision for each speed regime while keeping the overall system architecture relatively simple, as the same optoelectronic sensor is used for both sampling areas.
Solution Approach 2:
The patent applies local quality by assigning different functional characteristics to different regions of the optoelectronic sensor. The first sample area is optimized for low-speed measurement with higher spatial resolution, while the second sample area is optimized for high-speed measurement, allowing each region to have specialized characteristics for its intended operating condition.
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
The system provides precise tracking of vehicle movement in two-dimensional space, including yaw, with improved accuracy at low speeds and increased detection area at high speeds, using low-cost components and simplified processing, effectively addressing the limitations of existing systems.
Implementation Method 1
an optoelectronic sensor for receiving light from a first sample area on the road surface at a first location relative to the vehicle and generating a pixel pattern image of road surface irregularities in the first sample area
Data Source
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AI summary
Vehicle movement sensor (1) for a vehicle (2) travelling on a road surface (10). An optoelectronic sensor (8) from a first sample area (6) on the road surface (10) at a first location relative to the vehicle (2) and generating a pixel pattern image of road surface irregularities in the first sample area (6). A processor (9) for sampling pixel pattern images of the first sample area (6) and determining movement of the vehicle (2) using digital image correlation of sequential sampled pixel pattern images of the first sample area (6).