Road network state determination method and device, equipment and storage medium

A determination method and technology of road network, applied in the direction of neural learning method, road vehicle traffic control system, biological neural network model, etc., can solve the problems of insufficient comprehensive road network state analysis and low reliability, and achieve credibility High, scalable effects

Pending Publication Date: 2021-08-13
PCI TECH GRP CO LTD
View PDF4 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention proposes a method, device, equipment and storage medium for determining the state of the road network, s

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Road network state determination method and device, equipment and storage medium
  • Road network state determination method and device, equipment and storage medium
  • Road network state determination method and device, equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] figure 1 It is a flowchart of a method for determining the state of a road network provided by Embodiment 1 of the present invention. This embodiment is applicable to analyzing the traffic state and traffic mode of intersections and road sections in the road network, and judging the traffic state of the entire road network In the case of the situation, the method can be executed by the device for determining the state of the road network. The device for determining the state of the road network can be implemented by software and / or hardware, and can be configured in a computer device, such as a server, a workstation, a personal computer, etc. , the method specifically includes the following steps:

[0033] S110. Determine the association relationship between intersections and road sections in the road network.

[0034] The road network refers to a road system composed of various roads that are interconnected and interwoven into a network in a certain area. It is unders...

Embodiment 2

[0049] figure 2 It is a flow chart of a method for determining the state of the road network provided by Embodiment 2 of the present invention. This embodiment is based on the foregoing embodiments, and further refines the method for determining the state of the road network proposed by the present invention. This method can Executed by the means for determining the state of the road network, the means for determining the state of the road network can be implemented by software and / or hardware, and can be configured in computer equipment, such as servers, workstations, personal computers, etc., the method specifically includes the following step:

[0050] S210. Obtain geographical information of road sections in the road network.

[0051] In this embodiment, the geographical information of the road segment includes the geographical coordinates of the road segment on the road network map, the length of the road segment, the number of lanes of the road segment, the marked traf...

Embodiment 3

[0105] Figure 5 It is a schematic structural diagram of a device for determining the state of a road network provided by Embodiment 3 of the present invention. The device may specifically include the following modules:

[0106] An association relationship determination module 501, configured to determine the association relationship between intersections and road sections in the road network;

[0107] A graph neural network model building module 502, configured to construct a graph neural network model of the road network based on the association relationship;

[0108] A feature vector determination module 503, configured to train the vertices representing the road sections in the graph neural network model to obtain feature vectors of the vertices;

[0109] A similarity calculation module 504, configured to calculate the similarity between vertices based on the feature vector under the constraints of the attribute information of the road section;

[0110] A state determini...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a road network state determination method and device, equipment and a storage medium. The method comprises the steps of determining an association relationship between an intersection and a road section in a road network; constructing a graph neural network model of the road network based on the incidence relation; training the vertexes representing the road sections in the graph neural network model, and obtaining feature vectors of the vertexes; under the constraint of the attribute information of the road section, calculating the similarity between the vertexes based on the feature vectors; and determining intersections and road sections with correlated traffic modes and traffic states in the road network according to the similarity. According to the method, the feature vectors of the road sections are extracted from the graph neural network model, the attribute information of the road sections is combined with the feature vectors, the similarity between the road sections in the road network is calculated, and the state of the road network is evaluated according to the similarity, so that the state of the road network is evaluated from two dimensions of space and time; and the attribute information of the road section is integrated into the feature evaluation of the whole road network, so that the road network state can be analyzed more comprehensively.

Description

technical field [0001] Embodiments of the present invention relate to a road network traffic analysis technology, and in particular to a method, device, device and storage medium for determining a road network state. Background technique [0002] At present, in the urban road system (road network), information on traffic elements such as people, vehicles, and roads can be collected in real time, and the sources of urban traffic big data are increasingly abundant. Analysis is conducive to the effective management, control and operation of smart traffic, and is conducive to the evaluation of existing traffic control strategies and the deduction and evaluation of future traffic control strategies. [0003] Existing methods to analyze the state of the city's road network are mainly from the perspective of data statistics, that is, using historical traffic patterns and traffic state data to analyze the time factors that affect the current state of the road network, and simply usi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G08G1/01G06N3/04G06N3/08G06K9/62
CPCG08G1/0125G08G1/0129G08G1/0137G06N3/04G06N3/08G06F18/22
Inventor 金峻臣华文汪作为
Owner PCI TECH GRP CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap