Trailer Length Estimation via Radar Distribution Classification
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Solution Overview
Problem
Existing detection systems require several minutes to estimate the length of a trailer towed by a vehicle, which is inefficient and may pose safety risks due to delayed adjustments in the blind zone of the host vehicle.
Innovation Solution
A detection system that uses a radar unit and a controller circuit to determine the trailer length by classifying the distribution of detected targets into three classes and applying regression models to estimate the trailer length within a finite time period of about 1 minute.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar sensors are used to estimate trailer length, then measurement precision is improved, but loss of time increases due to requiring several minutes for stable estimation
Solution Approach 1:
The system performs preliminary classification of detected targets into three classes based on their distribution characteristics before performing the final length estimation. This preliminary action allows the system to select appropriate estimation methods in advance, reducing the time required for stable estimation while maintaining measurement precision.
Solution Approach 2:
The detection process is segmented into multiple stages: target detection, distribution determination, classification into three classes, and length estimation. By dividing the estimation process into discrete segments with specific algorithms for each class, the system achieves faster convergence and reduces the overall time required for stable estimation.
2Loss of time
If the detection process is accelerated to reduce time, then loss of time is reduced, but measurement precision deteriorates due to insufficient data collection
Solution Approach 1:
The system changes parameters based on the detected distribution class. For different classes of target distributions, different estimation algorithms and parameters are applied. This allows the system to achieve accurate measurements quickly by selecting the most appropriate estimation method for the current situation, rather than using a fixed time-based approach.
Solution Approach 2:
The estimation process is made dynamic by continuously monitoring the distribution of detected targets and adapting the estimation algorithm in real-time. The system transitions between different estimation modes based on the accumulated data characteristics, enabling fast convergence while maintaining precision through adaptive parameter adjustment.
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
The system enables rapid estimation of trailer length, reducing measurement errors to less than 1.5% and allowing for timely adjustments to the blind zone, thereby enhancing safety for drivers and other vehicles.
Implementation Method 1
A radar unit near the host-vehicle is configured to detect objects proximate the host-vehicle
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
A detection system includes a radar-unit and a controller-circuit. The radar-unit is configured to detect objects proximate a host-vehicle. The controller-circuit is in communication with the radar-unit and is configured to determine a detection-distribution based on the radar-unit. The detection-distribution is characterized by a longitudinal-distribution of zero-range-rate detections associated with a trailer towed by the host-vehicle. The controller-circuit is further configured to determine a trailer-classification based on a comparison of the detection-distribution and longitudinal-distribution-models stored in the controller-circuit. The trailer-classification is indicative of a dimension of the trailer. The controller-circuit determines a trailer-length of the trailer based on the detection-distribution and the trailer-classification.