Vehicle Drive Assist Risk Mapping for Scattered Road Objects
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Solution Overview
Problem
Existing drive assist systems struggle to effectively recognize and manage risk areas on the road caused by scattered objects, such as loads dropped from trucks, which can hinder stable vehicle travel and pose a diverse range of risks beyond frozen road surfaces.
Innovation Solution
A vehicle drive assist apparatus equipped with a stereo camera and image processing unit to identify scattered objects, set risk areas based on luminance value dispersion, and determine risk levels using entropy and height information distribution within these areas, enabling appropriate drive assist control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If drive assist systems use conventional object detection methods, then they can identify major obstacles, but they fail to detect small scattered objects that pose safety risks
Solution Approach 1:
The patent segments the detection process into multiple stages: first detecting prominent objects, then identifying small scattered objects around them through luminance value dispersion analysis. This segmentation allows the system to address different object sizes with specialized detection methods, resolving the contradiction between detecting major obstacles and small scattered objects
Solution Approach 2:
The patent introduces a new dimension of analysis by examining luminance value dispersion patterns around detected objects. Instead of relying solely on object size or traditional detection parameters, the system analyzes the spatial distribution of luminance values to identify scattered objects, adding a dimensional approach that enables detection of previously undetectable small objects
2Object-affected harmful factors
If drive assist systems expand detection coverage to include all potential risk areas, then they can identify scattered objects, but the system complexity increases
Solution Approach 1:
The patent applies preliminary action by first detecting prominent objects before analyzing for scattered objects around them. This staged approach allows the system to expand detection coverage efficiently by focusing computational resources on areas around already-detected objects, rather than uniformly analyzing the entire field of view, thus managing system complexity while maintaining comprehensive coverage
Solution Approach 2:
The patent implements local quality by applying different detection strategies to different spatial regions. Prominent objects are detected using conventional methods, while small scattered objects are detected through luminance dispersion analysis specifically in the vicinity of prominent objects. This localized approach enables comprehensive risk area detection without uniformly increasing system complexity across all detection areas
3Measurement precision
If drive assist systems use multiple detection parameters, then they can assess risk levels accurately, but the information processing requirements increase
Solution Approach 1:
The patent extracts and utilizes specific key parameters (luminance values and their dispersion patterns) from the visual data, rather than processing all available information. By focusing on the extraction of luminance characteristics around detected objects, the system achieves accurate risk level assessment while managing information processing requirements through selective parameter extraction
Data Source
AI summary
A vehicle drive assist apparatus is to be applied to a vehicle. The vehicle drive assist apparatus includes an object recognizer, a risk area setter, and a risk level setter. The object recognizer is configured to recognize an object in front of the vehicle. The risk area setter is configured to, when small objects are around the object, set a risk area including the small objects. The risk level setter is configured to set a risk level for the risk area with respect to the vehicle based on distribution of height information items within the risk area.