An Approach to Intelligent Traffic Management System using a Multi-agent System

Intelligent traffic management can be considered one of the most promising solutions to contemporary traffic problems. The traffic in transportation associated with emergency conditions including psychiatric improvement in transport network, allocation of variable traffic flows, reducing the number of the crowded traffic roads and paths as well as its negative effects (such as delays, waiting time, stress of driver, noise and air pollution, and blocking the assistive devices). This research has been used by new multi-agent systems to manage traffic. On the one hand, the proposed algorithm includes traffic flow improvement in emergency conditions until it is considered as real-time traffic information and in other hand, by preventing the increase the volume of a paths have effects in the reduce of crowded traffic situations at a specific time (for example, providing the proposed paths in the shortest time). In this article, the integrated environment is including JACK software for having a virtual agent behavior simulation. In general, the different simulation form in a distribution network can be used to display the crowded and traffic. In this article, the JACK software is used for having the explicit capabilities and supporting the common of this software in modelling the multi-agent systems, such as agents, design, event and capabilities. In addition, designing and analyzing of this interaction is simplest than the existed designs in JACK software. As a result of the proposed model, it seems reasonable that the proposed approach is different than previous works in each case. On the one hand, there are modeling system in the different tasks as intelligent agents dependent to present the simple and effective road network. In this case, it may correct and changes the actions of driver in emergency conditions by the concept of agent cooperation for achieving the common target.

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  • English

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  • Accession Number: 01670901
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 6 2018 10:01AM