Submap Projections for Cross-UTM Autonomous Vehicle Routing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Standard projection systems fail to accurately transform global coordinates to local Euclidean spaces of submaps, leading to significant projection errors, increased processing times, and resource consumption in mapping and routing for autonomous vehicles, especially when navigating across submaps in different Universal Transverse Mercator (UTM) zones.
Innovation Solution
Employing projections centered at arbitrary global points, such as latitude and longitude coordinates, to determine routes across submaps in different UTM zones, reducing errors and processing times by transforming local points to global coordinates using transverse Mercators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard projection systems (UTM zones) are used to transform global coordinates to local Euclidean spaces of submaps, then the mapping and routing system can handle large geographic areas, but significant projection errors occur when navigating across submaps in different UTM zones
Solution Approach 1:
The patent divides the map into multiple submaps, each represented by a local Euclidean space with its own projection centered at an arbitrary global point. This segmentation allows each submap to maintain high coordinate transformation accuracy independently, while the collection of submaps covers large geographic areas. The segmentation principle resolves the contradiction by localizing the projection error to individual submaps rather than accumulating across UTM zone boundaries.
Solution Approach 2:
Each submap uses a custom projection centered at an arbitrary global point (latitude and longitude coordinates) rather than fixed UTM zone centers. This local quality approach optimizes the projection accuracy for each specific submap region, minimizing projection errors locally while maintaining overall system coverage. The local projection centers are chosen to maximize accuracy for routes passing through each submap.
2Area of stationary object
If multiple UTM zones are used to cover large geographic areas, then the mapping system can represent extensive regions, but processing time and resource consumption increase
Solution Approach 1:
The patent segments the large geographic area into multiple submaps, each with its own local Euclidean space and projection. This segmentation enables parallel processing of route determination across submaps, reducing overall processing time compared to transforming coordinates across multiple UTM zones. The segmented approach allows the system to work with smaller, more manageable coordinate transformations simultaneously.
Solution Approach 2:
The patent pre-establishes projections for each submap centered at arbitrary global points before route determination begins. These preliminary projections are optimized for their respective submap regions, eliminating the need for complex real-time coordinate transformations when determining routes that cross submap boundaries. This preliminary action reduces processing time during actual route determination.
3Stability of the object's composition
If standard UTM zone projections are used, then the system can maintain consistent coordinate systems across zones, but significant projection errors occur at zone boundaries
Solution Approach 1:
The patent applies local quality by creating custom projections for each submap centered at arbitrary global points rather than using fixed UTM zone centers. This allows each submap to have optimized projection accuracy for its specific region, minimizing errors at submap boundaries. The local projection centers are strategically chosen to maximize accuracy for routes passing through each submap while maintaining overall coordinate system stability.
Solution Approach 2:
The patent uses arbitrary global points (latitude and longitude coordinates) as intermediary centers for each submap's projection. These intermediary centers act as mediators between the global coordinate system and local Euclidean spaces, providing smooth transitions at submap boundaries without the discontinuities inherent in fixed UTM zone boundaries. This intermediary approach maintains coordinate system stability while improving projection accuracy.
Data Source
AI summary
A method includes obtaining map data associated with a map of a geographic location including one or more roadways, the map including a first submap represented by a first local Euclidean space and a second submap represented by a second local Euclidean space. A route that includes a first roadway in the first submap and a second roadway in the second submap is determined using a first projection between a global coordinate system and the first local Euclidean space and a second projection between the global coordinate system and the second local Euclidean space. The route is provided to an autonomous vehicle (AV) for driving on the first roadway and the second roadway.