Synchronizing Neighboring Tiles in High Definition Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous agents and advanced driver assistance systems face significant computational challenges in matching features across neighboring tiles in high definition maps, as road features often span multiple tiles, requiring substantial resources for alignment.
Innovation Solution
A method utilizing grouped optimization to synchronize neighboring tiles by dividing them into groups, independently optimizing features that cross boundaries, and shifting borders to ensure joint optimization, thereby aligning road features across tiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optimization methods are used to match features across neighboring tiles, then feature alignment accuracy is improved, but computational resources required increase significantly
Solution Approach 1:
The patent divides the HD map into multiple tiles and further segments the optimization process by processing only the boundary features between adjacent tiles rather than optimizing all features simultaneously. This segmentation approach reduces the computational scope while maintaining alignment accuracy at tile boundaries where features are most critical for navigation continuity.
Solution Approach 2:
The patent applies different optimization strategies to different regions of the map. Specifically, it focuses computational effort on boundary regions where features cross between tiles, while using simpler methods for interior regions. This local quality approach ensures high accuracy where needed (at boundaries) while reducing overall computational resource consumption.
2Measurement precision
If all neighboring tiles are processed simultaneously for feature matching, then synchronization accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments neighboring tiles into groups based on their spatial relationships and processes them in parallel. By organizing tiles into manageable groups and processing boundary features between groups independently, the system achieves synchronized accuracy across all tiles while reducing total processing time through parallelization.
Solution Approach 2:
The patent performs preliminary identification and grouping of boundary features between tiles before executing the full optimization process. This preliminary action allows the system to prepare optimization tasks in advance and process them more efficiently, reducing overall processing time while maintaining synchronization accuracy.
3Measurement precision
If road features spanning multiple tiles are optimized jointly, then feature matchup accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the joint optimization of multi-tile road features into smaller, manageable sub-problems by processing one boundary region at a time. Instead of optimizing all crossing features across the entire map simultaneously, the system optimizes boundary features between adjacent tiles in discrete segments, reducing computational complexity while maintaining overall accuracy.
Solution Approach 2:
The patent applies partial optimization by focusing computational effort only on the boundary features where road features actually cross between tiles, rather than optimizing all features uniformly across all tiles. This partial action approach reduces computational complexity by concentrating resources only where needed for accurate feature matchup.
Data Source
AI summary
A method for synchronizing neighboring tiles in an electronic map is described. The method includes grouping neighboring tiles of the electronic map into a plurality of tile groups. The method also includes selecting a first tile group and a second tile group that border one another on at least a first tile in the first tile group and a second tile in the second tile group. The method further includes independently optimizing the first tile group and the second tile group if a feature crosses between the first tile group and the second tile group. The method also includes shifting a border of the first tile group and a border of the second tile group to join the first tile and the second tile in the second tile group or the first tile group.