Node-Based Map Matching for Probe Data Processing
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Solution Overview
Problem
Traditional map-matchers, particularly point-based systems, face challenges with accuracy, scalability, and efficiency when processing high volumes of probe points, leading to significant computational resource requirements and costs.
Innovation Solution
A node-based map matching method that sorts probe data into location traces, selects subsets of probe points within a threshold distance of nodes in a transportation network, and projects these points onto links to reduce computational resources and improve processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional point-based map matchers are used to process high volumes of probe points, then map matching can be performed, but computational resource requirements and processing time increase significantly
Solution Approach 1:
The patent segments the map matching process into node-based operations rather than point-based operations. By dividing the transportation network into nodes and links, and processing probe points in segments (location traces) rather than individually, the system reduces computational complexity while maintaining matching accuracy for high-volume datasets
Solution Approach 2:
The patent extracts and processes only the necessary subset of probe points within a threshold distance of nodes, rather than processing all probe points uniformly. This extraction approach filters out redundant computations and focuses computational resources only on probe points that need to be matched to the transportation network
2Quantity of substance
If traditional point-based map matchers process millions of probe points, then comprehensive map matching is achieved, but scalability is limited
Solution Approach 1:
The patent segments probe data into location traces and processes them in relation to discrete nodes and links in the transportation network. This segmentation allows the system to handle millions of probe points by breaking down the complex global matching problem into smaller, manageable local operations at each node
Solution Approach 2:
The patent changes the fundamental parameters of the map matching approach from point-based to node-based processing. By using nodes as the primary reference points and projecting probe points onto links between nodes, the system transforms the computational problem to achieve better scalability with larger datasets
Data Source
AI summary
An approach is provided for node-based map matching. The approach involves processing probe data to sort a plurality of probe points according to sessions keys. The approach also involves selecting a subset of the plurality of probe points within a threshold distance of a node of a map representation of a transportation network. The approach further involves initiating a map matching of the probe points of each session key to the map representation by, for said each session key: (1) determining a closest probe point to the node; (2) determining another closest probe point to a neighboring node, wherein the neighboring node is connected to the node by at least one link; and (3) projecting the plurality of probe points between the closest probe point to the node and the another closest probe point to the neighboring node onto the link.