HD Map Update via Satellite Imagery and Sensor Comparison
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Solution Overview
Problem
Current methods for updating high-definition maps for autonomous driving are inefficient in terms of time and effort, as they require direct measurement and mapping of changed locations, making it difficult to quickly reflect changes in road conditions and traffic policies.
Innovation Solution
A system and method that utilizes a vehicle electronic device to transmit data on consistency or differences with high-definition maps, and a server to determine update requirements, transmit revised policy information, and update map data based on positioning data from sensors, allowing for efficient and timely updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement and mapping of changed locations is performed, then map data accuracy is maintained, but time and effort consumption increases significantly
Solution Approach 1:
The patent uses satellite imagery and aerial photographs as copies of the actual road environment to update map data. Instead of performing direct physical measurement and mapping, the system acquires image data covering the target area, automatically extracts road information from these images, and updates the map database. This copying approach maintains measurement precision while dramatically reducing time and effort consumption.
Solution Approach 2:
The patent replaces mechanical field surveying methods with automated image processing systems. The system uses satellite images and aerial photographs combined with automatic road extraction algorithms to substitute for traditional mechanical measurement tools and manual mapping processes, achieving both accuracy and efficiency.
2Reliability
If comprehensive road condition monitoring is implemented, then map data currency is improved, but system complexity increases
Solution Approach 1:
The patent employs satellite imagery and aerial photographs that serve multiple functions simultaneously: they provide both visual documentation of road conditions and data for automatic road extraction. This multi-functional approach improves map data currency without proportionally increasing system complexity, as the same image data sources are used for multiple purposes.
Solution Approach 2:
The system implements automated road extraction from images, where the processing system itself performs the analysis without requiring manual intervention. The automatic extraction algorithms independently identify and extract road information from satellite and aerial images, reducing the need for complex manual processing systems while maintaining reliable map updates.
Data Source
AI summary
An embodiment system for updating high-definition maps for autonomous driving includes a vehicle electronic device configured to transmit determination result data of whether there is consistency with a high-definition map or analysis result data of a difference from the high-definition map, with respect to positioning data for a current location provided from a plurality of sensors according to a presence or an absence of policy information for a driving section and a server configured to provide the policy information and high-definition map data for the driving section to the vehicle electronic device, to determine whether an update is required based on the data received from the vehicle electronic device, and to update the high-definition map data based on the received positioning data.