Modeling Driver Speed Control with the Queuing Network-Model Human Processor (QN-MHP)
Driving is a complex task involving concurrent perceptual, cognitive, and motor activities. Computational cognitive modeling of driving behavior has great value for theoretical and applied research on driving. Queuing Network-Model Human Processor (QN-MHP) is a computational cognitive architecture that combines two complementary methods into cognitive modeling: the mathematical theories and simulation methods of queuing networks (QN) and the symbolic methods of the Model Human Processor (MHP). In this paper, using QN-MHP, we present a driver speed control model to represent the concurrent perceptual, cognitive, and motor activities involved in the task of driver speed control as truly concurrent processes. The simulation results suggest that this method is feasible and valid. This work makes a forward step toward the goal of comprehensive modeling of driving behavior with the QN-MHP.
Luzheng Bi1 Yili Liu
School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA
国际会议
17th World Congress on Ergonomics(第十七届国际人类工效学大会)
北京
英文
1-5
2009-08-09（万方平台首次上网日期，不代表论文的发表时间）