Autonomous Trailer Dynamics Assessment via Sensor Fusion
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately determining trailer loading configurations, particularly in quantifying dynamics such as the center of mass and moment of inertia, which are crucial for maintaining stability and handling.
Innovation Solution
The system employs sensors like radar or LiDAR to determine the turn rate of the trailer, calculate the center of mass, and assess the moment of inertia by analyzing the position of the trailer wheels relative to the towing vehicle, using a model that accounts for the coupling angle and distance from the coupling point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human crew detection methods are used to identify trailer loading issues, then operational simplicity is maintained, but measurement precision and reliability of trailer dynamics data deteriorate
Solution Approach 1:
The patent replaces human visual inspection and manual assessment with automated sensor systems (cameras, LiDAR, radar) and computational models that objectively measure trailer dynamics parameters such as center of mass position, moment of inertia, and sway characteristics, thereby achieving precise quantitative data without compromising operational simplicity
Solution Approach 2:
The system enables the autonomous vehicle to self-assess its trailer loading configuration by automatically collecting sensor data, processing it through dynamics models, and generating loading assessments without requiring human intervention, thus maintaining ease of operation while improving measurement precision
2Measurement precision
If automated sensor systems are deployed to measure trailer dynamics, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent employs multi-functional sensor systems that serve multiple purposes: the same sensors used for primary autonomous navigation and obstacle detection are also utilized to measure trailer dynamics parameters, thereby improving measurement precision without proportionally increasing device complexity
Solution Approach 2:
The system combines multiple sensing modalities (visual, range, velocity) and integrates them with physics-based dynamics models into a unified assessment framework, allowing comprehensive trailer dynamics measurement while managing system complexity through integrated processing
3Reliability
If detailed trailer loading assessment is performed, then reliability of vehicle control decisions improves, but loss of time in data processing increases
Solution Approach 1:
The system pre-computes trailer dynamics parameters and loading assessments during periods when the vehicle is stationary or moving at constant velocity, preparing control recommendations in advance so that real-time decision-making can rely on preprocessed data, thereby maintaining reliability while minimizing processing time delays
Solution Approach 2:
The system continuously collects and processes trailer dynamics data throughout operation, maintaining an updated assessment rather than performing discrete measurements, which allows for timely control decisions based on current loading conditions without requiring intensive batch processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables autonomous vehicles to accurately assess trailer loading dynamics, allowing for informed navigational actions such as speed adjustments and route planning to maintain stability and safety.
Implementation Method 1
determine a distance to a portion of the trailer from the data
Implementation Method 2
determine a doppler shift indicative of a speed of a wheel of the first wheel assembly from the data
Data Source
AI summary
Trailer detection is provided. A vehicle can determine a distance to a portion of the trailer from the time-of-flight sensor data. The vehicle can determine a doppler shift indicative of a speed of a wheel of a wheel assembly from the data. The vehicle can determine, based on the distance and the doppler shift, a wheelbase of the trailer.


