Electronic Map Updating Using Inter- and Intra-Image Matching
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Solution Overview
Problem
Current methods for updating electronic maps for autonomous driving, such as on-site surveying and mapping or using monitoring data from vehicles, fail to meet the requirements of high precision and continuous updates due to limited coverage and slow update speeds or low precision.
Innovation Solution
A method and apparatus that collect images from vehicles and execute inter-group and intra-group matching to update the location of map elements, incorporating visual data and geometrical data to improve positioning precision and facilitate fast updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-site surveying and mapping is used to update electronic maps, then mapping precision is improved, but coverage area and update speed deteriorate
Solution Approach 1:
The patent combines multiple image collection entities (vehicles, mobile devices) to collectively perform map updating tasks. By merging the capabilities of multiple collection entities, the system achieves both high precision through image matching and high productivity through parallel data collection from multiple sources, resolving the contradiction between precise mapping and fast updates.
Solution Approach 2:
The patent uses image data from collection entities as copies of the actual road scene to update electronic maps. Instead of direct on-site surveying, the system captures images with imaging devices, processes them through matching algorithms, and uses these image copies to update map information, thereby achieving fast updates without sacrificing precision.
2Productivity
If monitoring data from vehicles is used to update electronic maps, then update speed and coverage area are improved, but mapping precision deteriorates
Solution Approach 1:
The patent introduces image matching algorithms as an intermediary processing step between raw monitoring data collection and map updating. The system first collects images from vehicles, then uses sophisticated matching algorithms to accurately determine positions and update map elements, thereby maintaining high precision while preserving the fast update speed and wide coverage benefits of vehicle-based data collection.
3Measurement precision
If detailed navigation and positioning information is included in electronic maps, then positioning precision is improved, but data complexity increases
Solution Approach 1:
The patent segments map elements into distinct categories (road segments, traffic signs, lane lines, buildings) and processes each type separately through specialized matching algorithms. This segmentation allows the system to manage complex data by breaking it down into manageable components, maintaining high positioning precision while organizing data complexity in a structured manner.
Data Source
AI summary
A method, apparatus, and computer readable storage medium for updating an electronic map are disclosed. A method for updating an electronic map includes: acquiring a group of collected images collected by a collection entity and associated with a target map element in the electronic map, the target map element having a target image and a target location; executing inter-group matching between the group of collected images and the target image; executing intra-group matching among the group of collected images; and updating a location of a to-be-updated map element associated with the target map element based on the inter-group matching, the intra-group matching and the target location. In this way, the positioning precision of map elements can be improved.