DocumentCode :
3489065
Title :
A multi-agent architecture for a driver model for autonomous road vehicles
Author :
Brunet, Charles-Antoine ; Gonzalez-Rubio, Ruben ; Tétreault, Mario
Author_Institution :
Dept. de Genie Electr. et de Genie Inf., Sherbrooke Univ., Que., Canada
Volume :
2
fYear :
1995
fDate :
5-8 Sep 1995
Firstpage :
772
Abstract :
A look at the current state of driver models and driver related activities (parking, avoiding collisions, path selection, etc.) shows that driving is broken up in a series of small tasks. These must be executed in a coordinated manner by the driver, Their different nature suggest that each could be implemented by an artificial intelligence paradigm (for example: fuzzy logic, neural nets and knowledge based systems). We think that a multi-agent system integrating autonomous agents and enabling them to cooperate to solve problems that are beyond their individual capabilities is the architecture for a more complete driver model. In the long run, the driver model must integrate all characteristics of driver and vehicle, but for the moment current driver models are dedicated to some specific tasks executed by the driver, lateral and longitudinal control, parking and collision avoidance are examples. In this paper we propose an architecture for a generic multi-agent system used to develop the driver model
Keywords :
cooperative systems; intelligent control; road vehicles; artificial intelligence; autonomous road vehicles; collision avoidance; driver model; lateral control; longitudinal control; multi-agent architecture; parking; Artificial intelligence; Artificial neural networks; Autonomous agents; Collision avoidance; Fuzzy logic; Knowledge based systems; Multiagent systems; Remotely operated vehicles; Road accidents; Vehicle driving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 1995. Canadian Conference on
Conference_Location :
Montreal, Que.
ISSN :
0840-7789
Print_ISBN :
0-7803-2766-7
Type :
conf
DOI :
10.1109/CCECE.1995.526409
Filename :
526409
Link To Document :
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