Analysis of driver's characteristics based on internet of vehicles

Jian Qun Wang, Xiao Qing Xue, Ning Cao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The road traffic accidents caused huge economic losses and casualties, so it had been focused by the researchers. Lane changing characteristic is the most relevant characteristic with safety. The intent of lane changing was discussed. Firstly, the factors affecting the intent were analyzed, the speed satisfaction value and the space satisfaction value were proposed; then the data from the University of California, Berkeley was extracted and the number of vehicles changed lane more often and the vehicle ID were obtained; the BP neural network classification model was established, it was trained and testified by actual data. The results shown the method could predict the intent accurately.

Original languageEnglish
Title of host publicationAdvances in Transportation
Pages1148-1152
Number of pages5
DOIs
Publication statusPublished - 2014
Event3rd International Conference on Civil Engineering and Transportation, ICCET 2013 - Kunming, China
Duration: 14 Dec 201315 Dec 2013

Publication series

NameApplied Mechanics and Materials
Volume505-506
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference3rd International Conference on Civil Engineering and Transportation, ICCET 2013
Country/TerritoryChina
CityKunming
Period14/12/1315/12/13

Keywords

  • Classification model
  • Intent of lane changing
  • Space satisfaction value
  • Speed satisfaction value

Fingerprint

Dive into the research topics of 'Analysis of driver's characteristics based on internet of vehicles'. Together they form a unique fingerprint.

Cite this