Modeling Driver Lane Changing Based on the QN-MHP Cognitive Architecture
Computational models of driving behavior developed based on a cognitive architecture can provide better scientific understanding of driving, simulate driving behavior, quantitatively predict possible interference of in-vehicle tasks, and thus help develop human factors guidelines and tools for in-vehicle systems design. Driver lane changing is a common activity in driving. Therefore, modeling driver lane changing with a cognitive architecture should be an important component of cognitive models of driving behavior. In this paper, we develop a computational model of driver lane changing control with the Queuing Network-Model Human Processor (QN-MHP) cognitive architecture based on neuroscience and psychological findings. The simulation and experimental results from lane changing on straight and curved roads show that this model can perform the control process of lane changing well and the models control process is consistent with that of drivers.
computational model cognitive architecture driver lane changing control QN-MHP
LUZHENG BI JUNXING SHANG YILI LIU
School of Mechanical Engineering Beijing Institute of Technology Beijing 100081, China Department of Industrial and Operations Engineering University of Michigan Ann Arbor, USA
国际会议
重庆
英文
6-10
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）