Queuing network modeling of driver lateral control with or without a cognitive distraction task

Luzheng Bi*, Guodong Gan, Junxing Shang, Yili Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

In this paper, we propose a computational model of driver lateral control based on the queuing network cognitive architecture and the driver preview model about driver lateral control activities. This computational model was applied to model the dual tasks of driving with a cognitive distraction task. The comparison between human driver data and model simulation data shows that this computational model can perform vehicle lateral control well, and its performance is consistent with that of drivers under single-and dual-task driving conditions. Furthermore, we examine the effectiveness of some parameters of the model in representing different styles of driving and discuss the value of this computational model in facilitating the evaluation of vehicle dynamics and driver assistant systems and providing new insights into research on unmanned vehicle control techniques.

Original languageEnglish
Article number6227355
Pages (from-to)1810-1820
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Volume13
Issue number4
DOIs
Publication statusPublished - 2012

Keywords

  • Cognitive distraction
  • driver lateral control
  • multitask modeling of driving
  • queuing network (QN)

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