Multi-Node Composite Image System for Articulated Vehicles
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Solution Overview
Problem
Conventional surveillance systems for trucks lack a system architecture for image processing between interchangeable vehicle sections, making it difficult to generate a surround view of the entire vehicle due to varying numbers of cameras and calibrations, and insufficient electronic control unit (ECU) capacity.
Innovation Solution
A multi-node computer architecture with separate ECUs on the tractor and trailer portions of an articulated commercial vehicle, where each ECU processes and stitches images from associated cameras, omitting data from non-functioning cameras to generate a composite surround view, and communicates through a datalink to provide a consistent view to the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single ECU processes all camera images from interchangeable vehicle sections, then the system can generate a surround view, but the ECU capacity becomes insufficient when the number of cameras varies
Solution Approach 1:
The system divides the image processing function into multiple independent processing nodes (first processing node in tractor, second processing node in trailer). Each node processes images from its local cameras independently, then combines results through a datalink. This segmentation allows each ECU to handle a manageable subset of cameras regardless of total system size, resolving the capacity bottleneck.
Solution Approach 2:
The patent introduces a spatial dimension to the processing architecture by distributing ECUs across different vehicle sections (tractor and trailer). Instead of one centralized processor handling all inputs, the system creates a distributed network where processing occurs at multiple locations simultaneously, effectively scaling the system's processing capacity with vehicle configuration.
2Adaptability or versatility
If the system uses interchangeable vehicle sections with varying numbers of cameras, then the system becomes more versatile, but the complexity of image processing architecture increases
Solution Approach 1:
The patent creates a universal processing architecture where the same ECU design and processing logic can be applied to any vehicle section (tractor or any trailer type). The system uses standardized datalks and calibration data structures that work regardless of the specific camera configuration, allowing one architecture to serve multiple functions and configurations without requiring custom designs for each scenario.
Solution Approach 2:
The system handles varying camera configurations by dynamically adjusting processing parameters such as the number of active cameras, calibration data sets, and image stitching parameters. The architecture accepts camera count and calibration information as input parameters, automatically configuring the processing pipeline to match the actual hardware setup, thereby managing complexity through parameterization rather than structural redesign.
3Quantity of substance
If the system processes images from all cameras including non-functioning ones, then more data is available for processing, but image quality and reliability decrease
Solution Approach 1:
The system extracts and removes data from non-functioning cameras before processing. The first processing node identifies malfunctioning cameras and excludes their image data from the composite surround view generation. This extraction of defective data ensures that only reliable image inputs are combined and displayed, maintaining high reliability while still processing maximum available functional data.
Solution Approach 2:
The system implements a feedback mechanism where the processing node continuously monitors camera functionality and adjusts the processing pipeline accordingly. When a camera is detected as non-functioning, the system receives feedback about its status and automatically modifies the data flow to exclude problematic inputs, ensuring reliable operation without manual intervention.
Data Source
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AI summary
When employing a multi-node computing architecture for commercial articulated vehicles to generate a composite surround view of the vehicle, each processing node is associated with a vehicle segment. Each node has its own processor, memory and sensors. A master-slave relationship exists in the architecture. The segment processors collect, format, manage and package their local information. Communication between nodes is controlled by the master node, which can limit, adjust, subsample and alter the information and information flow from the slave nodes. The slave nodes can be freely recombined, using a pre-established communication standard or a format agreed upon at combination time.