A Distributed Approach for Coordination of Traffic Signal Agents

Ana L. C. Bazzan
2005 Autonomous Agents and Multi-Agent Systems  
Innovative control strategies are needed to cope with the increasing urban traffic chaos. In most cases, the currently used strategies are based on a central traffic-responsive control system which can be demanding to implement and maintain. Therefore, a functional and spatial decentralization is desired. For this purpose, distributed artificial intelligence and multi-agent systems have come out with a series of techniques which allow coordination and cooperation. However, in many cases these
more » ... e reached by means of communication and centrally controlled coordination processes, giving little room for decentralized management. Consequently, there is a lack of decision-support tools at managerial level (traffic control centers) capable of dealing with decentralized policies of control and actually profiting from them. In the present work a coordination concept is used, which overcomes some disadvantages of the existing methods. This concept makes use of techniques of evolutionary game theory: intersections in an arterial are modeled as individually-motivated agents or players taking part in a dynamic process in which not only their own local goals but also a global one has to be taken into account. The role of the traffic manager is facilitated since s/he has to deal only with tactical ones, leaving the operational issues to the agents. Thus the system ultimately provides support for the traffic manager to decide on traffic control policies. Some application in traffic scenarios are discussed in order to evaluate the feasibility of transferring the responsibility of traffic signal coordination to agents. The results show different performances of the decentralized coordination process in different scenarios (e.g. the flow of vehicles is nearly equal in both opposing directions, one direction has a clearly higher flow, etc.). Therefore, the task of the manager is facilitate once s/he recognizes the scenario and acts accordingly. Keywords: coordination of agents, evolutionary game-theory, learning in multi-agent systems, traffic signal control. and maintain increases with the number of traffic elements (traffic lights, detectors, specialized hardware, etc.). Another problem is the lack of interoperability among those elements, specially if purchased from different producers. Therefore, functional and spatial decentralization is desired. In fact, achieving spatial decentralization has been a major goal of traffic engineering [42] . Many authors have stressed the role of limited perception and communication capabilities and the need for implicit communication and learning mechanisms (e.g.
doi:10.1007/s10458-004-6975-9 fatcat:3v7y5iestragfb7bwoqjhd3v2y