Trailer Load Sensor Grid for Real-Time Distribution Control
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Solution Overview
Problem
Autonomous vehicles face challenges in adapting to shifts in trailer load distribution during travel, as existing systems assume predefined loading conditions, failing to account for unexpected load distributions.
Innovation Solution
A system comprising a grid of weight sensors on the cargo bed surface of an autonomous vehicle generates a weight distribution map, which is used to control vehicle operations and identify unsafe load conditions, enabling dynamic adjustment based on real-time load data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous truck operates based on predefined load distribution assumptions, then the control system is simple and easy to implement, but the system cannot account for shifts in load or unexpected loading conditions
Solution Approach 1:
The cargo bed surface is divided into a grid of multiple weight sensors, with each sensor monitoring a specific zone. This segmentation allows the system to detect load distribution across different regions independently, enabling detailed spatial awareness of cargo placement without requiring a single complex sensing system
Solution Approach 2:
The system transitions from assuming a single average load distribution to mapping load distribution across two spatial dimensions using a grid of sensors. This dimensional approach creates a weight distribution map that captures variations in load across the cargo bed surface, providing comprehensive adaptability to different loading scenarios
2Measurement precision
If a grid of weight sensors is deployed to detect real-time load distribution, then the system can accurately monitor and adapt to changing load conditions, but the device complexity and cost increase
Solution Approach 1:
The weight sensor grid serves multiple functions: detecting load presence, measuring load distribution, identifying load shifts, and providing spatial information for cargo monitoring. This multi-functionality allows a single sensor array to replace what would otherwise require multiple separate sensing and monitoring systems
Solution Approach 2:
The system continuously self-monitors load distribution and automatically adjusts vehicle operations based on detected conditions. The weight distribution map generated by the sensor grid enables the autonomous vehicle to autonomously adapt its control parameters without external intervention, maintaining accurate load awareness through continuous self-assessment
3Reliability
If the system continuously monitors weight data and generates weight distribution maps, then real-time load information is available for safe operation, but energy consumption increases
Solution Approach 1:
The system periodically updates the weight distribution map by sampling weight data at regular intervals rather than continuously processing every possible data point. This periodic monitoring approach maintains operational safety by detecting load shifts and unsafe conditions while reducing computational load and energy consumption compared to truly continuous monitoring
Data Source
AI summary
A system for monitoring a load distribution of an autonomous vehicle is provided. The system includes a processor in communication with a memory device. The processor is configured to receive weight data from a grid of weight sensors disposed on a cargo bed surface of the autonomous vehicle, generate a weight distribution map of the cargo bed surface based on the received weight data, the weight distribution map including an array of weight values, and control operation of the autonomous vehicle based in part on the generated weight distribution map.