Changing lane probability estimating model based on neural network

Jianqun Wang, Rui Chai, Qingyang Wu

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

14 Citations (Scopus)

Abstract

Changing lane is one of the methods to reach the destination faster and also could bring more highway traffic accidents. This study through the traffic feature recognition, cluster analysis, similarity measurements and estimation, analyzed the vehicle operation parameter before changing lane, proposed a changing lane probability estimating model which combines the SOM (Self-Organization Map) and BP (Back Propagation) artificial neural network and had passed the test of the Vissim micro traffic simulation data. This model contributes to the dynastic analysis and evaluation for changing lanes in the intelligent transportation system, the traffic accidents reduction. So it's a critical part for establishing the traffic safe system.

Original languageEnglish
Title of host publication26th Chinese Control and Decision Conference, CCDC 2014
PublisherIEEE Computer Society
Pages3915-3920
Number of pages6
ISBN (Print)9781479937066
DOIs
Publication statusPublished - 2014
Event26th Chinese Control and Decision Conference, CCDC 2014 - Changsha, China
Duration: 31 May 20142 Jun 2014

Publication series

Name26th Chinese Control and Decision Conference, CCDC 2014

Conference

Conference26th Chinese Control and Decision Conference, CCDC 2014
Country/TerritoryChina
CityChangsha
Period31/05/142/06/14

Keywords

  • changing lane probability
  • estimating model
  • neural network
  • traffic safety

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