TY - JOUR AU - Mouhcine, Elgarej AU - Mansouri, Khalifa AU - Mohamed, Youssfi PY - 2018 TI - Solving Traffic Routing System using VANet Strategy Combined with a Distributed Swarm Intelligence Optimization JF - Journal of Computer Science VL - 14 IS - 11 DO - 10.3844/jcssp.2018.1499.1511 UR - https://thescipub.com/abstract/jcssp.2018.1499.1511 AB - Proposing an efficient strategy to reduce traffic congestion is an essential step towards improvement as we take into consideration the unpredictable and dynamic infrastructure of the road network. With the advances in computing technologies and communications protocols, we can retrieve any type of data and receive in real-time the state of traffic congestion at each road using Electronic Toll Collection System (ETCS), Vehicle Traffic Routing System (VTRS), Intelligent Transportation System (ITS) and Traffic Light Signals (TLS). This study introduces a new distributed strategy that aims to optimize traffic road congestion in real-time based on the Vehicular Ad-Hoc Network (VANET) communication system and the techniques of the Ant Colony Optimization (ACO). The VANET is used as a communication technology that will help us create a channel of communication between several vehicles and routes. The techniques of the ACO is used to compute the shortest path that can be followed by the driver to avoid congested routes. The proposed system is based on a multi-agent architecture, in which all agents work together to monitor the road traffic congestion and help drivers quickly arrive at their destinations by following the best routes with less congestion. Simulation results show that the proposed method can reduce the total distance traveled and time taken in order to reach a destination, as compared to the classic “shortest path method” (based only on the distance).