Coupled Asset Status Detection Using Velocity Profile Matching
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Solution Overview
Problem
Current methods for determining coupled assets in mixed fleets, such as tractor units and trailers, are unreliable and costly, often requiring user input or dedicated sensors, and rely on GPS data that is not frequently synchronized, leading to processing challenges and inaccuracies.
Innovation Solution
A system that sets speed thresholds for tracking devices, initiates high-frequency GPS sampling when assets cross these thresholds, and compares timestamp data to identify matching velocity profiles, designating coupled assets and applying custom tracking rules and power-saving algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS data from tracked assets is used to determine coupled assets, then geolocation information is obtained, but the position reporting rate is not frequent enough to converge candidate matches in reasonable time and data points are not synchronized
Solution Approach 1:
The system implements periodic high-frequency GPS sampling at predetermined intervals to capture position data at multiple speed thresholds. This periodic sampling ensures synchronized data collection from coupled assets, allowing the system to converge on accurate coupling matches within reasonable timeframes despite the inherently lower base reporting rates of tracking devices.
2Reliability
If high-frequency GPS sampling is implemented to improve matching accuracy, then coupling detection reliability is improved, but processing requirements and costs increase
Solution Approach 1:
The system applies high-frequency sampling selectively only when assets cross predetermined speed thresholds, rather than continuously. This localized application of high-frequency data collection focuses processing resources on critical coupling events, maintaining high detection reliability while avoiding the excessive processing burden of continuous high-frequency sampling across all conditions.
Solution Approach 2:
The system changes the sampling frequency parameter dynamically based on speed threshold crossings. By adjusting the sampling rate from low (normal operation) to high (threshold crossing events), the system achieves reliable coupling detection during critical moments while minimizing overall processing requirements and associated costs.
3Measurement precision
If dead-reckoning calculations are performed to account for unsynchronized GPS data, then position accuracy is improved, but extensive processing is required and reliability is limited to straight-line movement at fixed speeds
Solution Approach 1:
The system performs preliminary synchronization of GPS data by capturing position information at multiple predetermined speed thresholds before attempting coupling matching. This preliminary action ensures that data from coupled assets are temporally aligned, eliminating the need for complex dead-reckoning calculations and enabling accurate matching regardless of movement patterns.
Data Source
AI summary
The present invention provides a system, method and apparatus for determining the status of coupled assets during transport. According to a first preferred embodiment, a method of the present invention preferably includes triggering a set of tracking devices to transmit time stamp data indicating when the tracked assets cross pre-set speed thresholds. The present invention preferably further includes comparing the received time stamp data to equivalent data points from other assets and identifying unique pairs of assets which crossed the same speed thresholds at similar times and positions (i.e. matching velocity profiles). The system then designates the unique pair of assets as coupled and may apply custom tracking rules and power saving algorithms to the coupled assets.