Trailer Angle Detection Using Rear Camera Image Processing
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Solution Overview
Problem
Existing automated vehicle control systems rely on dedicated angle sensors to detect the articulation angle of trailers, which can be obstructed, making manual maneuvering difficult and requiring alternative methods for accurate angle determination.
Innovation Solution
A trailer angle detection system utilizing a wide-angle camera to capture a rear field-of-view, transforming the signal into a top-down image, determining symmetry and shape matching values to estimate the articulation angle, and performing automated vehicle maneuvers based on this estimate without a dedicated angle sensor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated angle sensor is used to detect the articulation angle, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple functions (articulation angle detection, obstacle detection, and general rear field-of-view monitoring) into a single wide-angle camera system. The camera captures the entire rear scene, and the controller processes the image data to extract both the articulation angle information and obstacle information, eliminating the need for separate dedicated sensors for each function.
Solution Approach 2:
The wide-angle camera serves multiple purposes: it detects the articulation angle by analyzing the position of the trailer relative to the vehicle, simultaneously monitors for obstacles in the rear field-of-view, and provides overall situational awareness. This multi-functional approach replaces what would traditionally require multiple specialized sensors.
2Device complexity
If a wide-angle camera is used instead of a dedicated angle sensor, then the device complexity is reduced, but the measurement precision may worsen
Solution Approach 1:
The patent replaces the mechanical/dedicated angle sensor system with an optical imaging system (wide-angle camera) combined with computational image processing. The controller analyzes the captured image to determine the articulation angle by comparing the relative positions and orientations of the vehicle and trailer in the field-of-view, substituting direct mechanical measurement with optical observation and computational geometry.
Solution Approach 2:
The system transitions from direct one-dimensional angle measurement to two-dimensional image space analysis. The wide-angle camera captures a 2D representation of the 3D scene, and the controller processes this 2D image data to infer the 3D articulation angle, utilizing the additional spatial dimension provided by the wide-angle view to achieve accurate measurement.
3Ease of operation
If manual maneuvering is used with an obstructed view, then the ease of operation worsens, but the extent of automation is reduced
Solution Approach 1:
The system continuously captures images with the wide-angle camera, processes the image data to determine current articulation angle and detect obstacles, and uses this real-time feedback information to automatically adjust the vehicle's maneuvering. The controller receives ongoing input from the camera system and dynamically controls the vehicle's movement based on the detected conditions, creating a closed-loop control system that improves ease of operation through automation.
Data Source
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AI summary
A trailer angle detection system and method of detecting a trailer (102) of a vehicle (100) including a wide-angle camera (115) and a controller (110). The controller is configured to receive a signal from the wide-angle camera representative of an area behind the vehicle. The controller transforms the signal into a top-down image. The controller determines a first plurality of values. Each of the first plurality of values is indicative of an amount of symmetry in a region of the top-down image. The controller determines a second plurality of values. Each of the second plurality of values is indicative of how closely a shape in the top-down image matches a predetermined shape. Then, the controller determines an estimate of an articulation angle based on the first plurality of values and the second plurality of values. Then controller performs an automated vehicle maneuver based on the estimate of the articulation angle.