Intelligent control of vehicles: preliminary results on the application of learning automata techniques to automated highway system

Author

Ünsal, Cem ; Bay, John S. ; Kachroo, Pushkin

Author_Institution

Center for Transp. Theory, Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

fYear

1995

fDate

5-8 Nov 1995

Firstpage

216

Lastpage

223

Abstract

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results

Keywords

automated highways; finite automata; intelligent control; learning (artificial intelligence); learning automata; position control; road vehicles; artificial intelligence technique; automated highway system; collision avoidance; communication data; intelligent vehicle control; lateral control; learning automata; learning stochastic automata; on-board sensors; sensor; simulation; trajectory planning; unmodeled stochastic environments; Artificial intelligence; Automatic control; Communication system control; Intelligent control; Intelligent sensors; Intelligent vehicles; Learning automata; Stochastic processes; Stochastic systems; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 1995. Proceedings., Seventh International Conference on

Conference_Location

Herndon, VA

ISSN

1082-3409

Print_ISBN

0-8186-7312-5

Type

conf

DOI

10.1109/TAI.1995.479517

Filename

479517