Vehicle Surrounding Object Mark Merging for Detection Accuracy
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Solution Overview
Problem
Surrounding vehicle detection systems often misidentify vehicles due to low reflection intensity surfaces, leading to the generation of multiple object marks for a single vehicle, resulting in incorrect recognition.
Innovation Solution
A vehicle equipped with a surrounding vehicle detector and a processor that groups reflected points, identifies ideal shapes, and merges object marks into a single shape based on predefined conditions, such as alignment and size, to improve recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the surrounding vehicle detection device emits electromagnetic waves to detect reflected points, then the detection coverage is improved, but low reflection intensity surfaces cause missed detections leading to multiple object marks for a single vehicle
Solution Approach 1:
The patent merges multiple object marks that correspond to the same surrounding vehicle into a single unified object mark. The processor identifies that multiple detected object marks represent one vehicle and combines them, using the union of their respective surfaces to create a comprehensive representation that accounts for low reflection areas that were initially missed.
Solution Approach 2:
The patent performs preliminary identification of ideal shapes before final recognition. The processor identifies an ideal shape that represents the complete surrounding vehicle based on the surfaces defined by multiple object marks, then uses this pre-identified shape to guide the merging process and improve subsequent recognition accuracy.
2Measurement precision
If multiple object marks are generated for a single surrounding vehicle, then detection sensitivity is improved, but recognition precision deteriorates due to false identification as multiple vehicles
Solution Approach 1:
The patent implements a feedback mechanism where the processor continuously monitors object marks and identifies when multiple marks correspond to the same vehicle. The system uses the identified ideal shape as feedback to guide the merging process, continuously refining the recognition by comparing detected marks against the established ideal vehicle shape.
Solution Approach 2:
The patent transitions from treating object marks as separate two-dimensional detections to creating a unified three-dimensional representation. By identifying ideal shapes and merging marks based on surface unions, the system adds a dimensional perspective that reveals multiple marks are actually different facets of the same vehicle.
3Manufacturing precision
If the processor merges object marks into ideal shapes, then recognition accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies local quality by identifying and processing only the specific surfaces that need to be merged. Rather than reprocessing all object marks uniformly, the system focuses on the particular surfaces defined by each object mark and merges them selectively based on the identified ideal shape, reducing unnecessary computational overhead.
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
Enhances the precision of surrounding vehicle recognition by correctly merging object marks, reducing false identifications and improving the accuracy of vehicle detection.
Implementation Method 1
The surrounding vehicle detection device emits electromagnetic waves to the surroundings of a vehicle to detect reflected points of a surrounding vehicle present around a host vehicle
Data Source
AI summary
The vehicle includes a surrounding vehicle detector detecting reflected points of surrounding vehicles present around the vehicle by emitting electromagnetic waves to surroundings of the vehicle, and a processor configured to generate object marks by grouping the reflected points detected by the surrounding vehicle detector, and edit the generated object marks. The processor is configured to extract two object marks from the generated object marks, identify an ideal shape for when the two object marks are merged based on surfaces defined by the two object marks and able to be seen from the vehicle, and merge the two object marks into the ideal shape if predetermined merger conditions are satisfied.