Urban traffic jam identification method based on virus propagation theory

A technology of urban traffic and recognition methods, which is applied in the traffic control system of road vehicles, traffic control systems, traffic flow detection, etc., can solve the problems of a large number of marginal road sections and the prediction accuracy needs to be improved, and achieve the realization of data volume and information volume, Overcoming the need for data and computing power to great effect

Active Publication Date: 2021-10-22
SOUTHWEST JIAOTONG UNIV
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the results show that the prediction accuracy of the overall road network is high, the calibration of the parameters in the mode

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
  • Urban traffic jam identification method based on virus propagation theory
  • Urban traffic jam identification method based on virus propagation theory
  • Urban traffic jam identification method based on virus propagation theory

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The invention proposes a method for judging congestion based on the SIS model, which mainly involves two parts, namely, a traffic state identification method based on the HHT (Hilbert-Huang transform) model and a congestion propagation model based on the SIS theory.

[0022] The HHT method is a common method for analyzing nonlinear and non-stationary data, mainly including two stages: EMD (Empirical Mode Decomposition) and HSA (Hilbert Spectra Analysis). Generally speaking, the EMD model decomposes the original time series data into a limited number of oscillation modes according to its own local characteristic time scale. Each oscillation mode is similar to a harmonic function, and an intrinsic mode function IMF (Intrinsic Mode Function), and then use the HAS method to calculate the oscillation period of each IMF.

[0023] In the congestion propagation model based on the SIS virus propagation theory, (I) represents infected individuals, (S) represents uninfected indivi...

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 an urban traffic jam identification method based on a virus propagation theory. The method comprises the following steps: 1, establishing an urban traffic jam propagation model based on the SIS virus propagation theory; 2, calculating the congestion proportion of the road section; and 3, recognizing the state of the road section based on the HHT model. Compared with the prior art, the method has the following positive effects: 1) simplicity: a simple virus propagation process is used to describe space-time characteristics of congestion in an urban road network during propagation, and the defect that a microscopic traffic flow model needs great data and calculation capability can be overcome, and the defect that a macroscopic traffic flow model cannot describe the propagation process can be overcome; and 2) accuracy: the HHT model is used for recognizing the traffic state of a road section and judging whether congestion happens or not, the algorithm can capture the change rule of traffic data in time, all internal information of original data is basically reserved, and balance between the data size and the information amount is achieved to a certain degree.

Description

technical field [0001] The invention relates to a method for identifying urban traffic jams based on virus transmission theory. Background technique [0002] The complex network characteristics of the urban road network make it difficult to identify urban traffic congestion. In order to identify the congestion in the urban traffic network and explore the rules of congestion propagation, many scholars have established congestion propagation models based on micro-models and macro-models. In these models, microscopic models are used to represent the precise characteristics of vehicles or road segments, which are computationally demanding and difficult to implement in large-scale networks. [0003] Different from microscopic models, macroscopic models are often used to describe the changing characteristics of traffic parameters and their interrelationships, such as queuing theory, traffic wave model, and machine learning methods. Specifically, the traffic wave model and queuing...

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): G06Q10/06G06Q50/26G08G1/01G06N3/00
CPCG06Q10/067G06Q50/26G08G1/0133G06N3/006Y02T10/40
Inventor 刘澜陈玉婷毛剑楠黄豪晏启鹏
Owner SOUTHWEST JIAOTONG UNIV
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