Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Distributed problem solving and planning
Mutli-agents systems and applications
An Agent-Oriented Approach for the Dynamic Vehicle Routing Problem
IWAISE '08 Proceedings of the 2008 International Workshop on Advanced Information Systems for Enterprises
Multi-agent system in urban traffic signal control
IEEE Computational Intelligence Magazine
Cooperative agent navigation in partially unknown urban environments
Proceedings of the 3rd International Symposium on Practical Cognitive Agents and Robots
Abstract Architecture for Task-oriented Multi-agent Problem Solving
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Dynamic Origin/Destination matrices are one of the most important parameters for efficient and effective transportation system management. These matrices describe the vehicle flow between different points inside a region of interest for a given period of time. Usually, dynamic O/D matrices are estimated from link traffic counts, home interview and/or license plate surveys. Unfortunately, estimation methods take O/D flows as time invariant for a certain number of intervals of time, which cannot be suitable for some traffic applications. However, the advent of information and communication technologies (e.g., vehicle-to-infrastructure dedicated short range communications --V2I) to the transportation system domain has opened new data sources for computing O/D matrices. Taking the advantages of this technology, we propose in this paper a multi-agent system that computes the instantaneous and dynamic O/D matrix of any road network equipped with V2I technology for every time period and day in real-time. The implementation was done using JADE platform. The results show that the multi-agent system is able to obtain the instantaneous O/D matrix for any time period and day.