Vehicle Path Segmentation for Autonomous Navigation
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Solution Overview
Problem
Current autonomous driving systems face challenges in accurately identifying a clear path for vehicle navigation due to the computational intensity required for processing and classifying objects in complex road environments, often necessitating bulky and expensive equipment.
Innovation Solution
A method that segments images from a camera system to define a clear path by analyzing the likelihood of object presence rather than individually classifying objects, using a combination of image processing techniques such as likelihood analysis, patch-based analysis, and image difference calculations to determine the vehicle's path without the need for extensive object classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object recognition and classification methods are used to identify clear path, then navigation accuracy is improved, but computational processing time increases
Solution Approach 1:
The image is divided into multiple patches that are processed independently and in parallel. Each patch is analyzed for clear path characteristics without requiring full object recognition. The patches are then combined to form the complete clear path determination, enabling faster processing while maintaining navigation accuracy.
2Measurement precision
If comprehensive object classification is performed to identify clear path, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The method extracts only the essential clear path characteristics from image patches rather than performing comprehensive object classification. By focusing specifically on identifying clear path regions through color space analysis and patch comparison, the system achieves detection accuracy without requiring complex object recognition equipment.
3Measurement precision
If multiple image analysis methods are applied to segment clear path regions, then detection accuracy is improved, but computational burden increases
Solution Approach 1:
The system applies multiple image analysis methods to patches but only to the extent necessary for clear path detection. By processing patches independently and using targeted analysis methods rather than comprehensive image processing, the system achieves detection accuracy while reducing overall computational burden compared to analyzing the entire image with all methods.
Data Source
AI summary
A method for detecting a clear path of travel for a vehicle by segmenting an image generated by a camera device located upon the vehicle includes monitoring the image, analyzing the image with a plurality of analysis methods to segment a region of the image that cannot represent the clear path of travel from a region of the image that can represent the clear path of travel, defining the clear path of travel based upon the analyzing, and utilizing the clear path of travel to navigate the vehicle.