On-Board Map Integration Using Layer Discrepancy Evaluation
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Solution Overview
Problem
The integration of multiple horizontal maps from different sources into a single aircraft display can result in mismatches and display incorrect information due to differences in style, symbology, and layer structures, increasing pilot workload and potential safety risks.
Innovation Solution
An automated system and method that compares and integrates horizontal maps by stripping non-relevant data, analyzing common layers, and generating discrepancy maps to identify the best source maps for integration, using airspace-based comparisons rather than ownship coordinates, and providing alerts for discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple horizontal maps from different sources are integrated into a single display, then pilot workload is reduced and situational awareness is improved, but mismatches and incorrect information may be displayed due to differences in style, symbology, and layer structures
Solution Approach 1:
The system performs preliminary actions by automatically comparing source maps before integration and generating discrepancy maps that highlight potential mismatches. This advance analysis allows the system to identify and correct issues before they affect navigation, ensuring reliable integrated map display while maintaining reduced pilot workload.
Solution Approach 2:
The system implements feedback mechanisms through discrepancy maps and alerts that provide real-time information about mismatches between source maps. This feedback loop enables the system to automatically adjust or warn pilots about potential errors, maintaining both ease of operation and reliability by continuously monitoring and correcting integration issues.
2Productivity
If automated map integration is performed, then map comparison and selection is streamlined, but discrepancies between maps may not be detected without additional analysis
Solution Approach 1:
The system segments the map comparison process into distinct analytical stages: extracting common layers, generating discrepancy maps, and identifying mismatches. This segmentation allows automated integration to proceed efficiently while maintaining high precision in discrepancy detection by focusing analysis on specific map elements and their relationships.
Solution Approach 2:
The system introduces intermediary discrepancy maps as a mediating structure between source maps and the final integrated display. These intermediary products highlight mismatches and serve as a bridge for automated correction, enabling both high productivity through automation and high precision in discrepancy detection through systematic comparison.
3Manufacturing precision
If style data is removed from maps to enable comparison, then common layers can be accurately identified, but the original map appearance and characteristics are lost
Solution Approach 1:
The system segments map data into distinct components: style data and geographical data (layers). By separating these components, the system can accurately compare common layers without the干扰 of stylistic differences, achieving high precision in layer comparison. The original map styles are preserved separately and applied to the final integrated output, preventing information loss.
Solution Approach 2:
The system extracts style data from maps to enable objective comparison of geographical layers. This extraction allows precise identification of common layers and discrepancies without the influence of stylistic variations. The extracted style information is then re-applied to the integrated map, ensuring both accurate comparison and preservation of original map characteristics.
Data Source
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AI summary
A method includes receiving map image data of multiple horizontal input maps of an overlapping geographical area and arranged to be displayed on a display device on a vehicle. Each input map has style data and at least one layer associated with a different type of geographical data shown on the map. The method includes generating multiple plain maps comprising removing the style data from the map image data of each input map, and determining common layers between at least two of the plain maps showing the same type of geographical data. The method includes determining data of a discrepancy map of discrepancies between the common layers of the at least two plain maps and for each common layer of the at least two plain maps, and generating an error value of the at least two plain maps comprising using the discrepancy maps.