Optical Vehicle Movement Sensing for Low-Speed and GPS-Denied 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 pixel patterns 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 tracks vehicle movement by analyzing pixel pattern changes in successive images of the road surface. This intermediary approach bypasses the need for GPS satellite signals, providing reliable position tracking in shielded environments where GPS fails.
Solution Approach 2:
The patent replaces the radio-frequency-based GPS system with an optical imaging system that uses digital image correlation to measure vehicle displacement. This substitution of measurement methodology enables accurate position tracking without relying on satellite signals, solving the reliability issue in noisy and shielded environments.
2Measurement precision
If ABS tachometer is used for movement tracking, then accuracy is achieved at higher speeds, but resolution is too low for accurate positional determination in low-speed situations
Solution Approach 1:
The patent employs a dynamic sampling approach where the optoelectronic sensor captures images at adaptive intervals based on vehicle speed. At low speeds, more frequent sampling provides high-resolution position data, while at higher speeds, the system maintains accuracy through increased sampling rate, effectively covering the full speed range with appropriate resolution.
Solution Approach 2:
The system changes the sampling parameters (image capture frequency and integration time) based on vehicle speed conditions. This parameter adaptation allows the optical flow sensor to maintain measurement precision across varying speeds, overcoming the fixed-resolution limitation of ABS tachometers.
3Measurement precision
If road marking recognition is used to calibrate wheel rotation meter, then accuracy can be improved, but the system becomes dependent on consistent road markings which are not always available
Solution Approach 1:
The patent extracts the movement measurement function from dependency on external road features (markings) by using natural road surface texture and digital image correlation. This extraction makes the system self-sufficient, eliminating the need for external calibration references that may not be available on all roads.
Solution Approach 2:
The optical flow sensor system performs self-calibration and self-measurement by analyzing the relative motion of pixel patterns in successive images. The system does not require external road markings or pre-established reference frames, making it universally applicable across different road conditions without external assistance.
4Measurement precision
If high-resolution image processing is used to track road features, then movement can be determined, but complex multi-frame processing is required increasing device complexity
Solution Approach 1:
The patent uses a simplified copying approach where low-resolution images of the road surface are captured and compared between frames using digital image correlation. Instead of processing high-resolution images, the system works with downsampled pixel patterns that retain sufficient information for accurate movement measurement, significantly reducing computational complexity.
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 range at higher speeds, making it suitable for autonomous driving systems, especially in challenging environments.
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
Data Source
AI summary
Vehicle movement sensor for a vehicle travelling on a road surface. An optoelectronic sensor 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. A processor for sampling pixel pattern images of the first sample area and determining movement of the vehicle using digital image correlation of sequential sampled pixel pattern images of the first sample area.