Camera Mirror Trailer Wheelbase Detection From Image Features
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Solution Overview
Problem
Existing camera mirror systems in commercial trucks face challenges in accurately determining the trailer wheelbase length, especially when connecting trailers of different lengths, leading to imprecise determinations and reduced performance of automated and semi-automated vehicle systems.
Innovation Solution
A method and system using a camera mirror system to determine the trailer wheelbase length by receiving images from cameras, identifying features such as wheels, calculating two-dimensional distances, and converting these distances to three-dimensional measurements based on the trailer angle, using a conversion function and filtering techniques to ensure accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If kinematic models rely on a fixed trailer length parameter, then the system can operate with simplified assumptions, but the measurement precision deteriorates when trailers of different lengths are connected
Solution Approach 1:
The system dynamically changes the trailer length parameter based on detected trailer features. Instead of using a fixed trailer length assumption, the system identifies wheels and other features in camera images to calculate the actual trailer length, then updates the kinematic model parameters accordingly. This resolves the contradiction by allowing the system to maintain simplicity while adapting to different trailer configurations.
Solution Approach 2:
The system performs self-calibration by automatically detecting trailer features and determining trailer length without requiring manual input or pre-programming. The image processing system identifies wheels and calculates distances to determine the actual trailer configuration, enabling the kinematic model to self-adjust to different trailers.
2Adaptability or versatility
If the system uses image-based feature identification to determine trailer parameters, then the adaptability to different trailer lengths improves, but the device complexity increases due to additional image processing requirements
Solution Approach 1:
The system extracts only the essential features needed for trailer parameter determination from the camera images, specifically focusing on wheel identification and distance measurement. Rather than performing comprehensive image analysis, the system isolates and processes only the critical elements required for calculating trailer length and angle, reducing overall system complexity.
Solution Approach 2:
The system replaces traditional mechanical or manual trailer parameter input methods with optical image-based detection. Instead of requiring physical measurement tools or manual entry of trailer specifications, the system uses camera imaging and automated feature recognition to determine trailer parameters, simplifying the interaction while improving adaptability.
Data Source
AI summary
A method for determining a trailer detection parameter of a trailer including receiving an image from at least one camera at a controller. The at least one camera defines a field of view including at least a portion of a vehicle trailer. The method determines a trailer angle of the vehicle trailer relative to a tractor, identifies at least one feature in an image of the trailer, determines a two-dimensional distance from the at least one feature to a predefined position on the image, and converts the two-dimensional distance to a three-dimensional distance based at least in part on the determined angle. The three-dimensional distance is a trailer detection parameter of the trailer.