Surrounding Vehicle Cargo Recognition for Falling Object Risk
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle to accurately determine whether an object likely to fall from a surrounding vehicle is approaching a host vehicle without performing computationally intensive image processing.
Innovation Solution
A surrounding situation recognition device that utilizes statistical data on past falling objects to identify specific objects on surrounding vehicles and determines their likelihood of falling based on historical data without requiring extensive image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous image processing is performed to detect falling cargo, then detection accuracy is improved, but computational load increases significantly
Solution Approach 1:
The patent extracts only the essential features needed for falling object detection (object type classification based on statistical data) from the complete image processing pipeline. Instead of continuously analyzing all image data, the system extracts and processes only relevant statistical characteristics of potential falling objects, significantly reducing computational load while maintaining detection accuracy.
Solution Approach 2:
The system performs preliminary classification of objects based on statistical data about historical falling incidents. By pre-establishing criteria for what constitutes a falling risk object and classifying current objects against these criteria, the system avoids the need for continuous, computationally intensive real-time image processing while maintaining accurate detection.
2Power
If statistical data is used to identify falling objects, then computational load is reduced, but detection accuracy may deteriorate
Solution Approach 1:
The patent introduces statistical data as an intermediary between raw image data and falling object detection. Instead of directly processing images to detect falling objects, the system uses statistical data about historical falling incidents as a mediator to classify and identify potential falling objects, achieving both reduced computational load and maintained detection accuracy.
Solution Approach 2:
The system uses statistical data that copies and represents the essential characteristics of historical falling objects. By comparing current objects against these statistical copies rather than performing full image analysis, the system achieves accurate detection with minimal computational resources.
Data Source
AI summary
A surrounding situation recognition device determines whether an object mounted on a surrounding vehicle located in the vicinity of a host vehicle corresponds to a specific object which is an object where the number of cases processed in the past as a falling object on a road is greater than or equal to a threshold value, and determines whether an object likely to fall from the surrounding vehicle to the vicinity of the host vehicle exists based on the result of determination whether the object mounted on the surrounding vehicle corresponds to the specific object.