Autonomous vehicle control systems – a review of decision making

Veres, Sandor M., Molnar, Levente, Lincoln, Nicholas and Morice, Colin (2011) Autonomous vehicle control systems – a review of decision making Proceedings of the I MECH E Part I Journal of Systems & Control Engineering, 225, (2), pp. 155-195. (doi:10.1177/2041304110394727).


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A systematic review is provided on artificial agent methodologies applicable to control engineering of autonomous vehicles and robots. The paper focuses on some fundamentals that make a machine autonomous: decision making that involves modelling the environment and forming data abstractions for symbolic processing and logic-based reasoning. Most relevant capabilities such as navigation, autonomous path planning, path following control, and communications, that directly affect decision making, are treated as basic skills of agents. Although many autonomous vehicles have been engineered in the past without using the agent-oriented approach, most decision making onboard of vehicles is similar to or can be classified as some kind of agent architecture, even if in a naïve form. First the ANSI standard of intelligent systems is recalled then a summary of the fundamental types of possible agent architectures for autonomous vehicles are presented, starting from reactive, through layered, to advanced architectures in terms of beliefs, goals, and intentions. The review identifies some missing links between computer science results on discrete agents and engineering results of continuous world sensing, actuation, and path planning. In this context design tools for ‘abstractions programming’ are identified as needed to fill in the gap between logic-based reasoning and sensing. Finally, research is reviewed on autonomous vehicles in water, on the ground, in the air, and in space with comments on their methods of decision making. One of the main conclusions of this review is that standardization of decision making through agent architectures is desirable for the future of intelligent vehicle developments and their legal certification.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1177/2041304110394727
ISSNs: 0959-6518 (print)
Related URLs:
Keywords: autonomous vehicles, artificial intelligence, intelligent agents, control systems
ePrint ID: 149623
Date :
Date Event
31 August 2010Submitted
1 March 2011Published
Date Deposited: 30 Apr 2010 15:30
Last Modified: 18 Apr 2017 14:24
Further Information:Google Scholar

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