Traffic prediction method for Internet of Vehicles communication based on machine learning

A communication flow and machine learning technology, applied in data exchange networks, digital transmission systems, electrical components, etc., can solve the problem of time-consuming and labor-intensive, the distribution characteristics of data indicators are not well displayed, and the difficulty of multiple time series curves, etc. problem, to achieve good prediction performance, good prediction, and good generalization performance.

Active Publication Date: 2019-09-20
NANJING UNIV OF SCI & TECH
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, the two-step optimal selection method is a statistical method for predicting time series, but it can only detect and count based on a single time series, and it is relatively difficult for multiple time series curves
Another combined method combining wave theory analysis and spectrum analysis is to divide traffic data into thre

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 prediction method for Internet of Vehicles communication based on machine learning
  • Traffic prediction method for Internet of Vehicles communication based on machine learning
  • Traffic prediction method for Internet of Vehicles communication based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] In order to verify the validity of the present invention, the traffic flow rate data released by the traffic data platform is used to predict the traffic flow, as follows:

[0046] Using the all-weather data of 12 sections of Shanghai Yan'an Elevated Road from September 1 to September 7, 2018 released by the Shanghai Big Data Joint Innovation Laboratory (Transportation Field) platform, to predict the all-weather traffic on these sections on September 8 Traffic, that is, a 7-day training data set with a total of 60480 groups (train.csv), and a 1-day test data set with a total of 8640 groups (test.csv). The data set indicators include 8 categories: Traffic Flow, Week, Weather, Time, Speed, Traffic Volume, Traffic Index, and Section Place.

[0047] Use the isna function to judge whether each indicator has missing values, and use the len function to perform statistics on the training set data train.csv, including: the number count, mean, standard deviation std, minimum valu...

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 prediction method for Internet of Vehicles communication based on machine learning, and the method comprises the steps: selecting eight types of data indexes by utilizing a traffic speed database issued by a traffic data platform, and completing the all-weather traffic flow prediction through a random forest algorithm after parameter optimization; exporting an urban road vehicle traffic scene in a certain place by utilizing the openstreetmap, obtaining traffic data, configuring a communication simulation file, obtaining communication data, mixing the two kinds of data, and analyzing the relationship between the traffic flow and the communication flow; exporting a road section selected by a traffic data platform by utilizing openstreetmap, configuring a communication simulation file, acquiring communication data, selecting nine types of related indexes from flow speed data and communication data released by the traffic data platform, and performing communication flow prediction through a Bagging model. The method is good in generalization performance and high in accuracy, a reliable vehicle-mounted communication analysis method can be provided for later-stage utilization of economic and efficient data distribution, and the driving safety of vehicle users is enhanced.

Description

technical field [0001] The invention relates to the technical field of vehicle flow forecasting in urban road vehicle traffic scenarios, in particular to a method for predicting existing traffic data by using machine learning algorithms, and combining communication simulation to complete vehicle network communication flow forecasting method. Background technique [0002] Vehicular ad hoc network is a revolutionary development of new generation information technology relying on computer network, modern wireless communication and cloud computing, and it was developed to provide reliable in-vehicle communication through cost-effective data distribution. Vehicle communication can be used to reduce traffic accidents, traffic congestion, travel time, fuel consumption, etc. In-vehicle communication allows road users to be aware of their surroundings in the event of critical and dangerous situations that may occur to them by exchanging information. Therefore, the research on the co...

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): H04L12/24
CPCH04L41/147H04L41/145
Inventor 代俊韩涛王静赵惠昌
Owner NANJING UNIV OF SCI & 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