Modeling driver car-following based on the queuing network cognitive architecture

Lu Zheng Bi*, Yi Li Liu

*Corresponding author for this work

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

15 Citations (Scopus)

Abstract

Driver car-following control is a quite common activity in driving. Modeling driver car-following in a cognitive architecture can contribute to driving-related human factors research. Queuing Network-Model Human Processor (QN-MHP) is a computational cognitive architecture developed to represent human information processing as a queuing network on the basis of neuroscience and psychological findings. In this paper, using the QN-MHP cognitive architecture, we propose a driver car-following model to represent the concurrent perceptual, cognitive, and motor activities involved in the task of driver car-following. The simulation results show that this model can perform the control process of car-following well, and the results are consistent with those of driver control.

Original languageEnglish
Title of host publicationProceedings of the 2009 International Conference on Machine Learning and Cybernetics
Pages895-900
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Machine Learning and Cybernetics - Baoding, China
Duration: 12 Jul 200915 Jul 2009

Publication series

NameProceedings of the 2009 International Conference on Machine Learning and Cybernetics
Volume2

Conference

Conference2009 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityBaoding
Period12/07/0915/07/09

Keywords

  • Car-following
  • Cognitive architecture
  • Driving model
  • QN-MHP

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