Vehicle Radar Scanning Angular Resolution Adjustment
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Solution Overview
Problem
Existing external environment recognition systems for vehicles face high processing loads due to increased detection points, especially in scenarios with many objects on the road, leading to increased capacity of point cloud data and processing demands.
Innovation Solution
The system intermittently emits electromagnetic waves in the traveling direction of the vehicle, adjusting detection point density based on distance from the vehicle, with higher density for road surfaces far away and lower density for surfaces close to the vehicle, reducing the number of detection points required for recognition processing without compromising accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the in-vehicle detector scans and emits electromagnetic waves to detect external environment with many detection points, then the recognition accuracy of external environment is improved, but the processing load increases
Solution Approach 1:
The patent applies local quality by setting different detection point intervals in different spatial regions. Specifically, the detection point interval is set to be smaller (higher density) in regions farther from the vehicle and larger (lower density) in regions closer to the vehicle. This non-uniform distribution optimizes recognition accuracy where it is most needed while reducing processing load in regions where high density is less critical.
Solution Approach 2:
The patent implements dynamics by making the detection point interval adjustable and adaptive. The microprocessor dynamically determines the interval of detection points based on distance information, allowing the system to adapt the detection density to the actual environmental conditions and recognition requirements, rather than using a fixed uniform interval.
2Measurement precision
If the number of detection points is increased to improve recognition accuracy, then the detection precision is improved, but the capacity of point cloud data increases
Solution Approach 1:
The patent reduces point cloud data capacity by applying local quality principles - using smaller detection point intervals only where necessary (farther regions) and larger intervals where less precision is needed (closer regions). This creates a non-uniform distribution that maintains detection precision in critical areas while significantly reducing the total number of detection points and associated data capacity requirements.
3Measurement precision
If the in-vehicle detector acquires three-dimensional point cloud data frame by frame, then the recognition accuracy of moving objects is improved, but the processing time increases
Solution Approach 1:
The patent reduces processing time by applying local quality to the temporal-spatial distribution of detection points. By using smaller intervals (higher density) for farther objects and larger intervals (lower density) for closer objects in each frame, the system maintains recognition accuracy for moving objects at various distances while reducing the total number of points to process, thereby decreasing processing time.
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 reduces the total number of detection points used for recognition processing, thereby decreasing processing load while maintaining recognition accuracy of positions and object sizes, even in scenarios with complex road environments.
Implementation Method 1
an in-vehicle detector configured to scan and emit an electromagnetic wave in a first direction and as a second direction intersecting the first direction to detect an external environment situation around a subject vehicle
Data Source
AI summary
An external environment recognition apparatus including: an in-vehicle detector configured to scan and emit an electromagnetic wave in a first direction and as a second direction to detect an external environment situation around a subject vehicle; and a microprocessor configured to acquire road surface information based on a detection data of the in-vehicle detector. The in-vehicle detector acquires a three-dimensional point cloud data frame by frame, and the microprocessor is configured to perform: recognizing a surface of the road and a three-dimensional object on the road for each frame as the road surface information based on the three-dimensional point cloud data, and determining an interval of detection points of the three-dimensional point cloud data of a next frame as a scanning angular resolution of the electromagnetic wave based on a size of a predetermined object and a distance from the subject vehicle to the object.