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

Author

Bi, Lu-Zheng ; Liu, Yi-li

Author_Institution

Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China

Volume

2

fYear

2009

fDate

12-15 July 2009

Firstpage

895

Lastpage

900

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.

Keywords

automobiles; cognition; human factors; neurophysiology; queueing theory; QN-MHP; concurrent perceptual; driver car-following control; driving-related human factor; human information processing; motor activity; neurophysiology; queuing network cognitive architecture; queuing network-model human processor; Computational modeling; Computer architecture; Computer networks; Context modeling; Cybernetics; Human factors; Information processing; Machine learning; Neuroscience; Psychology; Car-following; Cognitive architecture; Driving model; QN-MHP;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2009 International Conference on

Conference_Location

Baoding

Print_ISBN

978-1-4244-3702-3

Electronic_ISBN

978-1-4244-3703-0

Type

conf

DOI

10.1109/ICMLC.2009.5212407

Filename

5212407