Coupled Vehicle Yaw Tracking With Optical-Kinematic Fusion
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Solution Overview
Problem
Existing methods for measuring the yaw angle between a vehicle and a trailer are sensitive to target conditions, weather, lighting, and environmental factors, and are inaccurate when the vehicle is reversing.
Innovation Solution
A method that combines optical tracking with kinematic modeling using a Kalman filter to estimate the yaw angle, incorporating multi-resolution and multi-modality approaches to enhance accuracy and robustness, utilizing existing vehicle sensors without requiring modifications to the trailer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera-based optical sensors are used to track the yaw angle, then the measurement can be obtained visually, but the measurement is sensitive to adverse weather, lighting and environmental conditions
Solution Approach 1:
The patent combines optical sensor data with odometry data from existing vehicle sensors to create a hybrid measurement system. This merging of measurement approaches allows the system to maintain accurate yaw angle tracking even when optical conditions are poor, as the odometry provides complementary information that is not affected by weather or lighting conditions.
Solution Approach 2:
The patent introduces a computational model that acts as an intermediary between the raw sensor data and the final yaw angle measurement. This model processes and fuses the optical and odometry data, filtering out the harmful effects of adverse conditions while preserving the essential measurement information.
2Measurement precision
If target-based methods are used to measure yaw angle, then the tracking can be performed with a camera, but the method is sensitive to target condition and placement
Solution Approach 1:
The patent extracts the essential measurement information from multiple data sources (optical sensors and odometry) rather than relying on a single target-based approach. This extraction of key information from diverse sources eliminates the need for careful target placement and condition monitoring while maintaining measurement precision.
Solution Approach 2:
The patent creates a universal measurement system that uses existing sensors on the towing vehicle for multiple purposes - both for navigation and for yaw angle measurement. This multi-functionality eliminates the need for specialized target equipment and makes the system adaptable to various towing configurations without requiring modifications to the towed vehicle.
3Ease of manufacture
If existing sensors on the towing vehicle are used, then no modification of the towed vehicle is required, but the measurement accuracy may be insufficient
Solution Approach 1:
The patent combines data from existing vehicle sensors (odometry) with optical sensor data to achieve measurement precision that exceeds what either sensor type could provide alone. This fusion of multiple data sources maintains ease of implementation while significantly improving accuracy.
Solution Approach 2:
The patent transforms the raw odometry data and optical data into a unified yaw angle measurement through computational processing. By changing the parameters and representation of the input data, the system extracts more precise information from the existing sensors than would be available through simple individual readings.
Data Source
AI summary
A method for providing a yaw angle (105a) between a first vehicle (110) coupled to a second vehicle (100), comprises: receiving an image of the first vehicle from a camera (101) mounted on the second vehicle; performing (210) a polar transformation on the image to form a polar image (400) in a polar space having an origin corresponding to a location of a pivot point (303) of the coupling (302) to the second vehicle in the received image coordinate space; estimating (230) an optical coupling angle by analysing the content of the polar image; receiving a signal from an odometer (102) mounted on the first or second vehicle; estimating a kinematic coupling angle from the signal and a kinematic model of the first vehicle and the coupled second vehicle; and combining the estimated optical coupling angle and the estimated kinematic coupling angle to provide the coupling angle.