Road network important intersection extraction method based on floating car data

Abstract

The invention provides a road network important intersection extraction method based on floating car data. Road network intersection data are extracted by using road network data according to the road network intersection characteristics, and the intersection types are subdivided according to the types of the road sections connected with the intersections; then O and D matching is performed on floating car traveling tracks based on the road network intersections, and the intersections closest to the traveling start and end points act as the traveling O and D; then taxi traveling route data based on the road sections are converted into the traveling data based on the intersections by using the extracted intersections; then the intersection route data are split and the traveling data are screened so as to eliminate the unreasonable data; and finally the intersection correlation is introduced to define and select the appropriate correlation parameter, the intersections having high influence on the traveling behavior are acquired under the condition that the traveling O point and D point or the OD are / is known and the difference is analyzed so as to extract the important intersections.

Description

technical field [0001] The invention relates to the technical field of traffic planning application, and more specifically, to a method for extracting important road network intersections based on floating car data. Background technique [0002] In recent years, with the travel of fine-grained datasets, new ideas have been provided for in-depth analysis of urban traffic. In traditional urban traffic analysis, road section analysis is the main focus. As an important part of urban road network, intersections are important considerations in road network planning, design and management. Good urban traffic operation must pay attention to Reasonable and effective management of intersections. In addition, due to its outstanding node performance, urban intersections are attracting more and more attention from researchers. Considering that they are important distribution centers for urban traffic flow, they are important decision-making points when travelers choose travel directions...

AI Technical Summary

Problems solved by technology

However, there are few related studies based on urban intersections, and researchers are currently studying the behavior of traffic participants based on the urban spatial structure.

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