Virtual Yard Mapping for Real-Time Trailer Space Occupancy
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Solution Overview
Problem
Managing trailer yards efficiently is challenging due to the difficulty in accurately identifying and associating assets, such as trailers, with specific parking spaces, especially when they are partially or fully positioned between boundaries, and determining their occupancy status in real-time.
Innovation Solution
A system and method utilizing a controller to create a virtual map of the yard, correlating image data from sensors with GPS coordinates, and determining asset positions and identities, allowing for the association of assets with bounded regions and issuing move commands based on occupancy thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to identify and track trailers in the yard, then operational simplicity is maintained, but measurement precision and real-time tracking accuracy deteriorate
Solution Approach 1:
The patent replaces manual mechanical tracking methods with an automated vision-based system using cameras, image processing algorithms, and computer vision techniques to detect, identify, and track trailer positions and orientations automatically, significantly improving measurement precision while maintaining manageable system complexity through software-based solutions
Solution Approach 2:
The system creates virtual copies of the physical yard environment through photogrammetry and image processing, generating 2D images and 3D models that represent the actual trailer positions and yard layout, enabling accurate tracking and management without direct physical measurement intervention
2Productivity
If the yard operates without automated asset tracking, then system complexity is low, but productivity and real-time management capability deteriorate
Solution Approach 1:
The controller system performs multiple functions including image acquisition, image processing, asset identification, position calculation, and virtual map generation within a single integrated platform, improving productivity while managing complexity through multi-functional design rather than separate dedicated systems for each function
Solution Approach 2:
The system enables self-service operation where the automated vision system independently performs asset tracking, position determination, and virtual map updates without requiring constant human intervention, thereby improving productivity while the standardized algorithms keep system complexity manageable
3Measurement precision
If traditional methods are used to determine asset occupancy status, then ease of operation is maintained, but measurement precision and real-time detection capability deteriorate
Solution Approach 1:
The patent replaces difficult manual detection methods with automated image processing and computer vision algorithms that analyze camera images to precisely determine asset positions, orientations, and occupancy status, improving measurement precision while the automation reduces the practical difficulty of detection
Solution Approach 2:
The system introduces image data as an intermediary between the physical asset and the detection system, using processed images and virtual representations to mediate the measurement process, thereby improving occupancy detection accuracy while simplifying the overall measurement task through intermediate digital representations
Data Source
AI summary
A method of associating at least one asset with a bounded region in a yard is presented, the method including determining a virtual map of the yard including one or more bounded regions, bounded regions of the one or more bounded regions being regions in the yard where the at least one asset may be placed; determining a correspondence between points on the virtual map and coordinates in the yard; receiving an image from an image sensor positioned in the yard, the image including one or more assets; based on a pose of the image sensor, the correspondence, and positions of the one or more bounded regions, determining, the positions of the one or more bounded regions in the image; updating the virtual map to indicate that at least one asset is present within the first bounded region.


