Road Network Matching via Strand Elimination and Fréchet Distance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for matching road network representations from different sources are limited in accuracy, particularly in dense urban environments, due to reliance on spatial proximity and orientation, leading to errors in determining vehicle flow rates and pollutant emissions.
Innovation Solution
A method that constructs a third representation of a transport network by eliminating strands using discrete Fréchet distance, allowing for robust and adaptable matching with reduced computational resources, and determining road traffic attributes such as vehicle flow, speed, and pollutant emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If road network representations from different sources are matched using spatial proximity and orientation, then the matching process is simple, but the accuracy is poor especially in dense urban environments
Solution Approach 1:
The patent introduces an intermediary representation (third road network representation) that serves as a mediator between two different road network representations. This intermediary uses a standardized set of attributes (traffic flow, speed, pollutant emissions) as common reference points to establish accurate correspondences between road arcs from different sources, resolving the matching accuracy problem without complicating the overall process
2Measurement precision
If road network representations are enriched with multiple parameters from different data sources, then the completeness and accuracy of traffic attribute determination is improved, but the complexity of integrating and matching these representations increases
Solution Approach 1:
The patent segments the road network representations into discrete road arcs with associated attributes, allowing systematic comparison and matching. By breaking down the complex task into arc-level operations with standardized attribute sets, the method manages complexity while maintaining comprehensive data integration from multiple sources
Solution Approach 2:
The patent transforms different parameter sets from various data sources into a unified attribute framework consisting of traffic flow, speed, and pollutant emissions. This parameter standardization enables consistent comparison and integration across different road network representations without requiring complex customization for each data source
3Use of energy by moving object
If traditional mapmatching methods are used to determine road arc correspondence, then the computational resources required are minimal, but significant errors occur in determining traffic attributes like vehicle flow and pollutant emissions
Solution Approach 1:
The patent creates a copied and standardized representation of road network attributes (third representation) that preserves the essential traffic characteristics while enabling accurate matching. This copied representation uses standardized attribute sets that can be reliably compared across different sources, achieving both computational efficiency and measurement precision
Data Source
Figure 1~3
Figure 4
Figure 5~6
AI summary
The present invention relates to a method for determining at least one attribute (ATT) of road traffic from at least two representations (RES A, RES B) of the transport network, at least one road traffic parameter being associated with one of the two representations (RES A, RES B) of the transport network. To determine the road traffic attribute, a third representation (RES C) of the transport network is constructed by means of a correspondence (COR) between the two representations of the transport network, the correspondence being implemented after a strand elimination step (ELI).