Satellite Image Road Area Comparison for Navigation Map Updates
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Solution Overview
Problem
Current navigation electronic maps fail to accurately and timely update road network data, leading to suboptimal route recommendations due to the lack of comprehensive and timely discovery of new roads, which affects user navigation experience.
Innovation Solution
A method involving the comparison of road areas from latest and historical satellite images to identify candidate updated roads, mapping these roads into road network data, and verifying their actuality through user trajectory analysis, ensuring accurate updates to the road network data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional road network data collection methods are used, then the system structure remains simple, but the timeliness and comprehensiveness of road updates are insufficient
Solution Approach 1:
The patent introduces satellite images as an intermediary data source to detect road changes. Instead of directly collecting road data from multiple complex sources, the system uses satellite imagery as a mediator to indirectly observe and identify new roads or road modifications, thereby improving data accuracy without proportionally increasing system complexity
Solution Approach 2:
The patent creates a virtual model of the road network by extracting road information from satellite images. This virtual road map serves as a copy or representation of the actual road network, allowing the system to identify updates by comparing the extracted features with existing road network data, thus improving detection capability without requiring direct physical access to all roads
2Reliability
If satellite image comparison is performed to identify candidate updated roads, then the comprehensiveness of road update detection is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent extracts only the necessary road-related features from satellite images rather than processing the entire image data. By selectively extracting road network features such as linear patterns, connectivity, and geometric characteristics, the system reduces the volume of data requiring comparison and processing, thereby decreasing processing time while maintaining comprehensive update detection
Solution Approach 2:
The patent divides the road network into discrete segments or features that can be independently extracted and compared. By segmenting the road network data and satellite image features into manageable units, the system can process and compare road updates more efficiently, reducing the overall computational burden and processing time
3Measurement precision
If user trajectory data is used to verify candidate updated roads, then the accuracy of identifying actual updated roads is improved, but the data processing complexity increases
Solution Approach 1:
The patent incorporates user trajectory data as a feedback mechanism to verify candidate updated roads. By analyzing whether user-generated location data actually traverses the candidate road segments, the system receives real-world validation feedback, thereby improving verification accuracy. The feedback loop compares expected trajectories on candidate roads with actual user trajectories to confirm or reject updates
Data Source
AI summary
The present application discloses a method and apparatus for identifying an updated road, a device and a computer storage medium, and relates to the field of big data technologies. A specific implementation solution is as follows: comparing a road area extracted based on the latest satellite image with a road area extracted based on a historical satellite image, to obtain a candidate updated road; mapping the candidate updated road into road network data according to a coordinate position of the candidate updated road; acquiring a user trajectory set corresponding to the candidate updated road within a recent preset period; and identifying, based on a matching result between the user trajectory set and the road network data, whether the candidate updated road is an actual updated road. Updated roads can be more accurately identified through the method according to the present application.