Weather Hazard Tile Mapping With Binary Polygon Labeling
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Solution Overview
Problem
Legacy map-based systems face challenges in transitioning from polygon-based to tile-based systems, as tiles within tile-based maps may be partially covered by polygons, leading to inaccurate labeling and reduced map quality.
Innovation Solution
An apparatus and method that determine a subset of tiles within a tile map that define a weather condition by analyzing attribute data, including functional classes, proportion covered by the polygon, road density, and hazard intensity, using a tile score to accurately represent weather-based hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tiles within a tile-based map system are partially covered by polygons representing weather hazards, then the system can be adapted for parallel processing and improved efficiency, but the labeling accuracy and map quality deteriorate
Solution Approach 1:
The patent segments the map into discrete tiles and uses binary labeling (0 or 1) for each tile to represent weather hazard presence. This segmentation allows parallel processing of individual tiles while maintaining accurate hazard representation through the binary attribute that indicates whether a tile is fully or partially covered by hazard polygons.
Solution Approach 2:
The patent changes the representation parameter from continuous polygon geometry to discrete binary tile attributes. By converting weather hazard representation into binary tile attributes (present/absent), the system enables efficient parallel processing while preserving essential hazard information through the binary state that reflects partial or full coverage.
2Productivity
If binary representation is used for weather hazards in tile maps, then processing efficiency is improved, but information about hazard intensity and functional classes is lost
Solution Approach 1:
The patent adds additional dimensions to the binary tile representation by incorporating tile scores and multiple attribute types (functional class, road density, hazard intensity). This multi-dimensional approach allows the system to process tiles efficiently in parallel while retaining rich hazard information through scored attributes that go beyond simple binary presence/absence.
Solution Approach 2:
The patent creates a composite representation combining binary tile attributes with continuous hazard intensity data and functional class information. This composite structure integrates the efficiency of binary processing with the richness of detailed hazard characteristics, allowing both parallel processing and information retention.
3Reliability
If all tiles partially covered by polygons are labeled to define weather conditions, then hazard coverage is improved, but false positives increase and map quality decreases
Solution Approach 1:
The patent implements feedback through tile scoring mechanisms that evaluate multiple attributes (functional class, road density, hazard intensity) to determine the appropriate binary label. This feedback loop prevents false positives by considering the significance and context of hazard coverage rather than simply labeling all partially covered tiles, thereby maintaining both hazard coverage and map quality.
Solution Approach 2:
The patent applies different labeling decisions to different tiles based on their specific characteristics and hazard coverage attributes. Rather than uniform labeling of all partially covered tiles, the system evaluates each tile's functional class, road density, and hazard intensity to make localized quality decisions that avoid false positives while maintaining necessary hazard coverage.
Data Source
AI summary
An apparatus, method and computer program product are provided for providing a the map including a binary representation of a weather-based hazard. In one example, the apparatus receives data indicating a polygon defining a region being impacted by a weather condition and overlays the polygon on a tile map. The apparatus receives attribute data indicating one or more functional classes of one or more road portions within each tile of the tile map that is partially covered by the polygon and determines a subset of tiles within the tile map that defines the weather condition based on the attribute data.