Road Network Maneuver Ranking for Faster Map Updates
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Solution Overview
Problem
Existing navigation systems face challenges in accurately and efficiently updating digital maps due to the complexity of road network structures, particularly in densely populated areas, leading to prolonged processing times and inaccuracies in path predictions.
Innovation Solution
A method for ranking maneuvers in a road network by associating values with each maneuver based on predefined criteria, such as path cost, and updating these values based on selected paths to reduce redundant calculations and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If graph modeling with complex algorithms is used to extract information from road networks, then measurement precision of traffic volume estimation is improved, but device complexity and processing time increase
Solution Approach 1:
The patent segments the road network into local subgraphs centered at each node, rather than processing the entire network. This segmentation allows complex algorithms to be applied locally to smaller subsets of nodes and edges, reducing overall computational complexity while maintaining estimation accuracy for each local area.
Solution Approach 2:
The patent pre-calculates and stores the topology matrix for the road network in advance. This preliminary action eliminates the need to repeatedly compute topological relationships during traffic volume estimation, significantly reducing processing time and algorithmic complexity while preserving measurement precision.
2Measurement precision
If large volumes of traffic data are used for accurate estimation, then measurement precision is improved, but loss of time and computational resources increase
Solution Approach 1:
The patent extracts only the essential topological information from large volumes of traffic data by constructing a topology matrix that captures node and edge relationships. This extraction process filters out redundant data while retaining the critical structural information needed for accurate traffic volume estimation, reducing processing time without sacrificing precision.
Solution Approach 2:
The patent transforms raw traffic data into a different parameter representation through the topology matrix, which encodes network structure in a compact form. This parameter transformation allows accurate estimation using reduced data volumes by leveraging topological relationships rather than processing exhaustive traffic datasets.
3Measurement precision
If comprehensive road network structure evaluation is performed to estimate expected traffic volume, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent divides the comprehensive road network evaluation into localized assessments around each node using segmented subgraphs. This segmentation enables parallel processing of multiple node evaluations simultaneously, improving productivity while maintaining comprehensive structural analysis for accurate traffic volume predictions.
Solution Approach 2:
The patent performs preliminary construction of the topology matrix that pre-organizes road network structure information. This preliminary action enables rapid querying and evaluation of network structures during map updates, significantly improving productivity while preserving the comprehensive analysis needed for measurement precision.
Data Source
AI summary
A method and a system include associating a value with each of one or more maneuvers available at a central node of the set of nodes, selecting a path between a pair of nodes of the set of nodes based on a predefined criterion, and changing the value associated with a respective maneuver from the one or more maneuvers at the central node when the respective maneuver is part of the selected path.