Traffic congestion prediction method and system based on traffic congestion propagation model

A traffic congestion and propagation model technology, applied in the field of intelligent transportation, can solve problems such as low traffic congestion prediction efficiency, increased travel time of vehicle owners, and inaccurate traffic congestion analysis results.

Active Publication Date: 2017-03-22
SHENZHEN UNIV +1
View PDF7 Cites 55 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a traffic jam prediction method and system based on a traffic jam propagation model, aiming at solving the problem of traffic jam prediction in the prior art generally relying on people's subje

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
  • Traffic congestion prediction method and system based on traffic congestion propagation model
  • Traffic congestion prediction method and system based on traffic congestion propagation model
  • Traffic congestion prediction method and system based on traffic congestion propagation model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] In order to make the object, technical solution and effect of the present invention more clear and definite, the present invention will be further described in detail below. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0066] The present invention also provides a flow chart of a preferred embodiment of the traffic jam prediction method based on the traffic jam propagation model, as figure 1 As shown, the methods include:

[0067] Step S100 , acquiring the historical trajectory of the vehicle, performing path matching, and calculating the passing speed of the vehicle passing through the first road section.

[0068] During specific implementation, adopting road style among the present invention is to adopt node-arc section model (N-E) to represent, and wherein node n∈N represents road crossing, lane change point, main and auxiliary road junction, bus station, sub...

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 traffic congestion prediction method and system based on a traffic congestion propagation model. The method comprises: a historical track of a vehicle is obtained and a passing speed of the vehicle when passing through a first road section is calculated; according to the passing speed, a vehicle driving threshold is calculated; if an instantaneous driving speed of the current vehicle is lower than the vehicle driving threshold, traffic congestion is determined; and a road section with the monthly traffic congestion occurrence frequency larger than a predetermined frequency is determined to be a frequent traffic congestion section, a congestion sub graph is generated based on the frequent traffic congestion section, and the congestion sub graph is calibrated based on the probability of concurrence of traffic congestion of all connected sections and then a traffic congestion probability graph model is generated to predict a traffic congestion situation. Therefore, the accurate road traffic state can be extracted by using multi-source track big data, thereby completing the urban traffic congestion propagation analysis and discovering a traffic congestion source. Therefore, traffic congestion occurrence is reduced and the trip cost of the vehicle owner is saved.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a traffic congestion prediction method and system based on a traffic congestion propagation model. Background technique [0002] At present, the number of motor vehicles in the city continues to increase, the traffic pressure increases sharply, and traffic congestion often occurs in some areas, which brings great challenges to the smooth operation of urban traffic and exacerbates energy and environmental problems related to transportation. Clarifying the source and transmission mechanism of traffic congestion can relieve traffic congestion and ensure the smooth flow of urban traffic. Traditional traffic congestion propagation analysis methods generally use the experience of traffic experts to analyze, extract and predict possible traffic congestion based on the structure of the road network. Due to the lack of a reliable traffic congestion propagation model, i...

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): G08G1/01
CPCG08G1/0133
Inventor 涂伟黄练朱家松韩国华林钰龙周鹏李清泉
Owner SHENZHEN 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