A traffic state recognition method at intersections based on spatio-temporal analysis

A technology of traffic status and identification method, which is applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc., and can solve the problems of inability to directly guide signal control strategy, inability to describe vehicle dynamic information in detail, data isolation, etc. , to achieve the effect of comprehensively enriching the basic source data

Active Publication Date: 2022-01-04
NANJING LES INFORMATION TECH
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most of the eigenvectors selected for traditional traffic state recognition are based on the basic data of single-section flow and occupancy characteristics collected by coil detection, geomagnetic detection, and microwave detection, or vehicle queuing characteristics in a single detection area. The dynamic information of vehicles in the transition section cannot represent the real-time traffic operation status of the intersection well, and the most important thing is that these data are isolated from the signal release status data, and the result requirements for traffic status recognition (that is, the establishment of traffic signal control and grooming strategy), the results of such identification cannot directly guide the specific implementation of signal control and grooming strategies for relevant technical personnel

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
  • A traffic state recognition method at intersections based on spatio-temporal analysis
  • A traffic state recognition method at intersections based on spatio-temporal analysis
  • A traffic state recognition method at intersections based on spatio-temporal analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] The invention discloses a traffic signal coordination control method that automatically adjusts the period and the green signal ratio, and its steps are as follows: figure 1 shown, including the following steps:

[0037] (1) Data collection, (2) Preprocessing step, (3) Feature vector selection and definition step, (4) Classifier design step.

[0038] Combined with the specific application of traffic engineering, each actual operation step is explained as follows.

[0039] (1) Data collection

[0040] 1) This method provides an interface to collect the spatial data sent by the traffic flow equipment. The data collection mode of the traffic flow equipment is a detection method for the space 2 section 1 area of ​​the entrance road. The schematic diagram is as follows figure 2 shown. Each lane has two detection sections and a detection area. The two detection sections are respectively located about 0.5 meters before the stop line and at the end of the channelization. Th...

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 provides an intersection traffic state recognition method based on spatio-temporal analysis, including data collection, preprocessing steps of feature vector selection and definition steps, and classifier design. Firstly, the eigenvectors of traffic state recognition are obtained through spatio-temporal analysis technology, that is, the spatial traffic flow data and time real-time signal data are refined and deeply fused in stages to obtain value parameters that are more suitable for the traffic state, and then the obtained eigenvectors are analyzed. Carry out learning and training to automatically identify traffic conditions.

Description

technical field [0001] This patent relates to the technical field of traffic state recognition through computer software. Background technique [0002] Urban road traffic congestion has become one of the main social problems plaguing major cities around the world. It not only brings a lot of inconvenience to people's daily work and life, but also restricts economic growth, accelerates the deterioration of urban environment, etc., seriously affecting sustainable development of cities. Timely and accurate identification of traffic congestion in the road network is of great significance for formulating reasonable and effective traffic signal control strategies. Finding out the features that can effectively realize classification and recognition and better fit the traffic state from many features is the key and primary problem that needs to be solved urgently. [0003] Most of the eigenvectors selected for traditional traffic state recognition are based on the basic data of si...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G08G1/065G06K9/00
Inventor 沈阳程健郝建根顾怀中何华英张俊张继锋苏子毅江超阳
Owner NANJING LES INFORMATION TECH
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