Decreasing Traffic Congestion in VANETs Using an Improved Hybrid Ant Colony Optimization Algorithm

Abstract

Vehicular Ad-hoc Network (VANET) is a definitive form of mobile ad-hoc network (MANET), which delivers data communication in a vehicular environment, using wireless transmission. Its fundamental goal is to increase the service quality of Intelligent Transportation Systems (ITS), such as road safety, logistics, and environmental kindliness, as well as information interchange. Smart cities are encountering problematic traffic congestion, particularly in developing countries. This paper presents an Improved Hybrid Ant Colony Optimization (IHACO) algorithm for decreasing congestion in smart cities. The objective of the proposed scheme is to choose a best routing path during rush hours by providing an optimal path. The scheme also introduces the IHACO algorithm to improve QoS for ITS. This algorithm (IHACO) differs from other algorithms, such as particle swarm optimization (PSO), in terms of pheromone update processes, which makes it more efficient. Also, the ant colony hybrid routing protocol (ACOHRP) protocol is introduced to improve the service quality of intelligent traffic systems (ITS). It delivers superlative efficiency through a better origination of packet delivery ratio, throughput, and end-to-end delay. Simulation-based testing is performed using Matlab simulation. It was found that traffic congestion time decreased gradually when using IHACO, unlike with other algorithms. The computed results demonstrated that the IHACO algorithm offers improved performance in terms of reliability, period, distance, and throughput, compared with different algorithms presented in this paper.