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DOI: 10.14569/IJACSA.2019.0101039
PDF

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

Author 1: Shamim Akhter
Author 2: Md. Nurul Ahsan
Author 3: Shah Jafor Sadeek Quaderi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 10, 2019.

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Abstract: This paper focuses on Sumo Urban Mobility Simulation (SUMO) and real-time Traffic Management System (TMS) simulation for evaluation, management, and design of Intelligent Transportation Systems (ITS). Such simulations are expected to offer the prediction and on-the-fly feedback for better decision-making. In these regards, a new Intelligent Traffic Management System (ITMS) was proposed and implemented - where a path from source to destination was selected by Dijkstra algorithm, and the road segment weights were calculated using real-time analyses (Deep-Neuro-Fuzzy framework) of data collected from infrastructure systems, mobile, distributed technologies, and socially-build systems. We aim to simulate the ITMS in pragmatic style with micro traffic, open-source traffic simulation model (SUMO), and discuss the challenges related to modeling and simulation for ITMS. Also, we expose a new model- Ant Colony Optimization (ACO) in SUMO tool to support a multi-agent-based collaborative decision-making environment for ITMS. Beside we evaluate ACO model performance with exiting built-in optimum route-finding SUMO models (Contraction Hierarchies Wrapper) -CHWrapper, A-star (A*), and Dijkstra) for optimum route choice. The results highlight that ACO performs better than other algorithms.

Keywords: Intelligent Traffic Management System (ITMS); Simulation of Urban Mobility (SUMO); traffic simulation; Contraction Hierarchies Wrapper (CHWrapper); Dijkstra; A-star (A*); Deep-Neuro-Fuzzy Classification

Shamim Akhter, Md. Nurul Ahsan and Shah Jafor Sadeek Quaderi, “Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System” International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101039

@article{Akhter2019,
title = {Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101039},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101039},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {10},
author = {Shamim Akhter and Md. Nurul Ahsan and Shah Jafor Sadeek Quaderi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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