Ant colony optimization algorithm with Internet of Vehicles for intelligent traffic control system

Vehicles present on the Internet of Vehicles (IoV) can communicate with each other in order to determine the status of the road and vehicle in real time. These parameters are used to estimate the average speed and identify the optimal route to reach the destination. However, the government traffic departments are unable to use these valuable traffic data and thus more traffic jam, congestion and road accident occurs. In order to overcome this issue, this paper proposes an effective traffic control system with the help of IoV technology. The proposed method is demonstrated in the study are of Vellore district, Tamil Nadu, India. The street maps are segmented into number small number of distinct maps. Ant colony algorithm is applied to each map in order to find the optimal route. In addition, Fuzzy logic based traffic intensity calculation function is proposed in this paper to model the heavy traffic. The proposed IoV based route selection method is compared with the existing shortest path selection algorithms such as Dijikstra algorithm, Kruskal's algorithm and Prim's algorithm. The experimental results proved the good performance of the proposed IoV based route selection method.