A Case of Multiagent Decision Support: Using Autonomous Agents for Urban Traffic Control
IBERAMIA '98 Proceedings of the 6th Ibero-American Conference on AI: Progress in Artificial Intelligence
Multiagent traffic management: an improved intersection control mechanism
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Mobile agents for network management
IEEE Communications Surveys & Tutorials
Automated traffic light system for road user's safety in two lane road construction sites
WSEAS Transactions on Circuits and Systems
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
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For a intelligent traffic system (used for controlling traffic lights at intersections) to be useful in practice it needs to be adaptive to outer situation and to be scalable for different urban areas and streets. That is because patterns of the traffic networks and intersections are very diverse and changing in time. In this research scalability and adoptability have been in our center of interest. Other parameter which is very important in controlling traffic lights is prediction of traffic. This prediction would require having the big picture of the flowing traffic and thus centralized kind of Control (which conflict with scalability). Our aim was to design a model that is scalable and adaptive and at the same time has a sort of prediction mechanism. To achieve this we have worked on a model with high abstraction which has three levels of control. Every intersection is controlled by its own traffic situation, its neighbor intersections recommendation and a mobile agent that goes through different intersections in a particular section in the urban area and has a wider view of the traffic.