Collision Avoidance Sensing with Weighted Multi-Zone Detection
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Solution Overview
Problem
Conventional collision avoidance systems (CAS) face challenges in accurately determining the speed or distance of approaching objects due to interference from environmental noise, and either radar-based systems suffer from misjudgment or image recognition systems struggle with precision.
Innovation Solution
A combined radar and image recognition system for a carrier that includes a processor to detect objects in multiple areas, calculate collision probabilities based on weights and lighting states, and output alarm messages when thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If radar technology is used for detecting objects, then the detection range is extended, but misjudgment occurs due to environmental noise interference
Solution Approach 1:
The patent combines radar detection with image recognition technology to create a hybrid system. The radar provides detection range while the image recognition module validates targets to eliminate false positives from environmental noise, thus maintaining both extended detection range and high reliability
Solution Approach 2:
The image recognition module acts as an intermediary between the radar detection and the collision probability calculation. It validates radar-detected objects by analyzing visual characteristics, filtering out noise-induced false detections before they affect the final collision assessment
2Reliability
If image recognition technology is used for detecting objects, then the visual identification is improved, but the determination of speed or distance becomes inaccurate
Solution Approach 1:
The patent merges image recognition with radar measurement capabilities. The image recognition module provides accurate visual identification while the radar component simultaneously provides precise speed and distance measurements, combining the strengths of both technologies
3Device complexity
If a single detection area is used, then the system complexity is reduced, but the collision probability calculation lacks precision
Solution Approach 1:
The patent divides the detection space into multiple concentric detection areas (first detection area, second detection area, third detection area) with different weights. This segmentation allows the system to assign different collision probabilities to objects at different distances, significantly improving calculation accuracy while maintaining manageable system complexity through structured zonation
Data Source
AI summary
A CAS and a collision avoidance method are provided. The collision avoidance method includes: detecting, by a radar, a first detection area and a second detection area to generate a detection result of a target object, where the second detection area includes the first detection area and is greater than the first detection area; determining whether the target object invades the first detection area or the second detection area based on the detection result; in response to determining that the target object invades the second detection area but does not invade the first detection area, calculating a first collision probability based on a first weight and the detection result; in response to determining that the target object invades the first detection area, calculating the first collision probability based on a second weight and the detection result; determining whether to output an alarm message based on the first collision probability.