Map-Centric Map Matching Reduces Spatial Search Complexity
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Solution Overview
Problem
Existing map matching techniques are computationally expensive due to the proportional number of spatial searches required for each probe point, especially in large datasets, which limits their efficiency in real-time applications and scalability.
Innovation Solution
Implementing a map-centric map matching technique that reduces the number of spatial searches by basing them on the length of road segments rather than the number of probe points, allowing for more efficient projection of probe points onto road segments using defined vertices and spatial search separation distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If probe-centric map matching is used to ensure each probe point is matched to the closest road segment, then matching accuracy is improved, but the number of spatial searches becomes proportional to the number of probe points, increasing computational cost
Solution Approach 1:
The patent inverts the traditional probe-centric approach by implementing a map-centric approach where spatial searches are conducted from road segments to probe points rather than from each probe point to road segments. This inversion changes the search paradigm from N probe points × M road segments to K road segments × average probe points per segment, significantly reducing computational complexity while maintaining matching accuracy
Solution Approach 2:
The patent segments the road network into discrete road segments and organizes probe points spatially relative to these segments. By dividing the search space into manageable road segment units and using spatial indexing structures, the system efficiently groups and processes probe points by their associated road segments rather than treating each probe point independently
2Reliability
If spatial searches are conducted for each probe point to identify the closest road segment, then complete coverage is achieved, but execution time and computational resources increase substantially for large datasets
Solution Approach 1:
The patent performs preliminary organization of road segments and probe points into spatial data structures before conducting matching operations. By pre-indexing road segments and pre-grouping probe points by their associated road segments using spatial indexing, the system eliminates the need for repeated full-space searches and achieves complete coverage efficiently
Solution Approach 2:
The patent introduces spatial indexing structures as intermediaries between probe points and road segments. These indexing structures act as mediators that efficiently associate probe points with their corresponding road segments without requiring direct pairwise comparisons, thus maintaining complete coverage while reducing execution time
3Quantity of substance
If traditional map matching is used to process large probe datasets, then comprehensive analysis is achieved, but scalability is limited due to proportional computational requirements
Solution Approach 1:
The patent changes the fundamental parameter of the search approach from probe-point-driven to road-segment-driven. This parameter change transforms the computational complexity from O(N×M) where N is probe points and M is road segments, to a more scalable approach where complexity depends on the number of road segments and average probe points per segment, enabling the system to handle large datasets efficiently
Data Source
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AI summary
A method, apparatus and computer program product are provided to process probe data in accordance with a map-centric map matching technique. In the context of a method, a plurality of vertices are defined along a polyline representative of a road segment such that the polyline includes one or more edges. Each edge extends between a pair of neighboring vertices. For each vertex of a respective edge, spatial searches are conducted to identify each probe point within a region about a respective vertex. For each probe point identified within a region about a respective vertex, a determination is made as to whether the probe point satisfies a projection criteria in order for the probe point to be projected onto the edge or one of the neighboring vertices between which the edge extends.