Safe Area Monitoring With Refined Obstacle Boundary Detection
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Solution Overview
Problem
Conventional anti-collision systems in vehicles are excessively sensitive due to discrepancies between identified and actual obstacle boundaries, leading to frequent erroneous determinations and safety disruptions.
Innovation Solution
A monitoring method that generates a modified area close to the obstacle boundary, using a two-stage determination process to accurately assess whether the obstacle invades the safe area, reducing erroneous determinations and enhancing driving safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If object detection technology is used to identify obstacles, then obstacle detection capability is improved, but measurement precision deteriorates due to boundary discrepancy between identified and actual obstacle areas
Solution Approach 1:
The patent segments the obstacle detection process into two distinct stages: first, object detection technology identifies the obstacle and generates an initial obstacle area; second, contour recognition technology processes the obstacle boundary to generate a refined obstacle contour. This segmentation allows each technology to operate optimally in its specialized domain, with contour recognition correcting the boundary precision issues of object detection.
Solution Approach 2:
The patent introduces contour recognition technology as an intermediary processing step between object detection and collision determination. This intermediary refines the rough obstacle boundary from object detection into a precise obstacle contour that accurately represents the actual obstacle boundary, thereby resolving the measurement precision problem without sacrificing detection capability.
2Area of stationary object
If the identified obstacle area is used for collision determination, then detection coverage is improved, but reliability deteriorates due to excessive sensitivity and false warnings
Solution Approach 1:
The patent divides the collision determination process into two sequential stages: first, determine whether the obstacle area intersects with the safe area; second, determine whether the refined obstacle contour intersects with the safe area. This segmentation ensures that both the broader detection coverage and the precise boundary information are utilized, improving reliability by reducing false positives while maintaining comprehensive detection.
Solution Approach 2:
The patent implements a feedback mechanism where the results from obstacle area intersection detection feed into the more precise obstacle contour intersection detection. This two-stage feedback process allows the system to efficiently filter out obvious cases while applying more computationally intensive contour analysis only when necessary, improving overall reliability without excessive computational burden.
3Productivity
If conventional obstacle area determination is used, then processing speed is improved, but measurement precision deteriorates leading to erroneous determinations
Solution Approach 1:
The patent applies preliminary action by first performing the faster object detection to identify obstacles and generate initial obstacle areas. This preliminary step quickly screens the environment for potential obstacles, and only when obstacles are detected does the system proceed to the more time-consuming contour recognition process. This preliminary action maintains processing speed while ensuring precision when needed.
Solution Approach 2:
The patent segments the processing pipeline into speed-optimized and precision-optimized stages. Object detection technology provides rapid initial identification, while contour recognition technology provides precise boundary determination. This segmentation allows the system to maintain high processing speed for most scenarios while achieving high measurement precision when obstacles are present.
Data Source
AI summary
A monitoring method for a safe area, performed by a processing module having a processor and a pre-established image identification model, includes the following steps. An input image is generated corresponding to a predefined viewing direction of a driving target, and the input image has an image corresponding to an obstacle. A safe area is generated in the input image. A predetermined route is generated, and a continuous area that does not belong to the obstacle from a predetermined range extended from the predetermined route is defined to generate a modified area, so that in a situation that the predetermined range includes a part of an obstacle, a part of a boundary of the modified area corresponds to a part of a contour of the obstacle. Then a step is executed to determine whether the safe area is entirely included in the modified area.


