Autonomous Driving Map Feedback for GPS Error Correction
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Solution Overview
Problem
Existing technologies lack a definite specification for accurate road information generation, error correction, and updating of road information necessary for safe and precise autonomous driving.
Innovation Solution
An autonomous driving support system that generates road information, corrects errors, and updates road information by comparing camera recognition information with a predetermined road map, using a controller to generate vehicle control signals for various vehicle systems, and integrating data from multiple autonomous vehicles to enhance accuracy and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If road information is periodically corrected and updated for autonomous driving, then the accuracy and safety of autonomous driving is improved, but there is no definite specification for accurate road information generation, error correction, and updating
Solution Approach 1:
The system collects camera recognition information from multiple autonomous vehicles and feeds it back to correct and update road map information. This feedback mechanism ensures continuous improvement of road information accuracy by comparing actual observations with stored map data, resolving the contradiction between reliability improvement and system complexity through an organized feedback loop.
Solution Approach 2:
The server performs multiple functions including collecting data from multiple vehicles, generating road information, correcting errors, and updating road maps within a single system. This multi-functional approach consolidates what could be separate complex systems into one unified platform, improving reliability while managing complexity through functional integration.
2Reliability
If camera recognition information from multiple autonomous vehicles is integrated to update road information, then the reliability of road information is improved, but the complexity of data processing and integration increases
Solution Approach 1:
The system merges camera recognition information from multiple autonomous vehicles into a unified road information dataset. By combining data sources and consolidating processing operations at the server level, the system improves reliability through multiple observations while managing integration complexity through centralized data fusion rather than distributed complex coordination.
3Measurement precision
If GPS errors are corrected based on landmark comparison between road map information and camera recognition information, then navigation precision is improved, but the complexity of error correction processes increases
Solution Approach 1:
Landmarks serve as intermediary reference points between GPS coordinates and camera recognition data. The system uses these intermediate features to bridge the gap between different data sources, enabling accurate GPS error correction without requiring direct complex processing between all data elements, thus improving precision while managing correction complexity.
Data Source
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AI summary
The present disclosure relates to an autonomous driving support apparatus and method capable of generating road information for autonomous driving, correcting an error, and updating the road information. The autonomous driving support apparatus of the present disclosure includes at least one autonomous vehicle and a server. The autonomous vehicle senses a traveling road to generate camera recognition information including road information, signpost information, traffic light information, construction section information, and future route information. The server analyzes at least one piece of camera recognition information received from a controller of the at least one autonomous vehicle to update predetermined road map information, and transmits the updated road map information to the at least one autonomous vehicle.