Vision navigation for driver cognitive model in ACT-R architecture

Author

Cao, Jie ; Wang, Hong

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China

fYear

2010

fDate

7-9 July 2010

Firstpage

946

Lastpage

951

Abstract

Cognitive Science is widely studied as a high degree of cross-disciplinary. Various models are presented by several popular architectures. ACT-R (Adaptive Control of Thought-Rational) architecture is one of most popular cognitive architectures. A new combination of cognitive science and artificial intelligence is studied in this paper. Signal serials in visual modules are usually artificial defined in many cognitive models, including driver cognitive models. Vision based automatic navigation is explored for visual module of driver cognitive model. Signal serials in visual modules are provided by automatic vision based navigation systems from real driving video, and used for driver model in ACT-R architecture. Results are compared. Experimental result shows that the applying of vision navigation on cognitive model in ACT-R architecture is reliable.

Keywords

adaptive control; artificial intelligence; cognition; computer vision; driver information systems; navigation; ACT-R architecture; adaptive control of thought-rational architecture; artificial intelligence; automatic vision based navigation systems; cognitive science; driver cognitive model; Algorithm design and analysis; Cognition; Driver circuits; Pixel; Roads; Shape; Vehicles; ACT-R architecture; driver cognitive model; vision navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-8041-8

Type

conf

DOI

10.1109/COGINF.2010.5599773

Filename

5599773