Home > Published Issues > 2020 > Volume 11, No. 2, May 2020 >

Dynamic Parking Guidance Architecture Using Ant Colony Optimization and Multi-agent Systems

Khaoula Hassoune 1, Wafaa Dachry 2, Fouad Moutaouakkil 1, and Hicham Medromi1
1. High National School of Electricity and Mechanics (ENSEM), Hassan II University, Casablanca, Morocco
2. Faculty of science of Hassan I University, Settat, Morocco

Abstract—Nowadays, drivers have great difficulty finding a parking space easily due to the traffic congestion in some areas and the distribution of car parks within the city. This work aims to design a new system that will allow a vehicle driver to find the best route between his real-time position and parking with available places in a specific area. Our system is based on a distributed swarm intelligence strategy using the ant colony algorithm, cloud system, and multi-agent systems to offer an optimal solution toward the nearest car park in the city. Our solution will improve the use of available parking in the city.
Index Terms—Ant Colony Optimization (ACO), cloud system, multi-agent systems, traffic road

Cite: Khaoula Hassoune, Wafaa Dachry, Fouad Moutaouakkil, and Hicham Medromi, "Dynamic Parking Guidance Architecture Using Ant Colony Optimization and Multi-agent Systems," Journal of Advances in Information Technology, Vol. 11, No. 2, pp. 58-63, May 2020. doi: 10.12720/jait.11.2.58-63

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.