Intelligent traffic management system using Ant Colony Optimization and Internet of Things. (1st June 2022)

• Record Type: Journal Article
• Authors: Dureja, Ajay; Sangwan, Suman
• Is Part Of: International journal of communication systems. Volume 35:Number 13(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-01
• Subjects: Ant Colony Optimization -- Intelligent Transportation System -- Internet of Things -- Internet of Vehicles -- VANET; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.5248
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Miniaturization of Internet of Things (IoT) enabled devices has led to advancement in Intelligent Transportation System. Some of the challenges for efficient traffic management are connection of vehicles through an IP based infrastructure for transportation, reliable, and flexible traffic control management, maintaining quality of services for video streaming applications in Internet of Vehicles and many more. Today there is a need of an efficient transportation system with improved efficiency of traffic safety and lower traveling costs. An intelligent traffic control system using Ant Colony Optimization (ACO) algorithm has been proposed and analyzed in this paper. Proposed algorithm has been compared with existing state of art algorithms in terms of average waiting time and average traveling time. Abstract : Today there is a need of an efficient transportation system with improved efficiency of traffic safety and lower traveling costs. An intelligent traffic control system using Ant Colony Optimization (ACO) algorithm has been purposed and analyzes in this paper. For efficient traffic management a framework has been proposed in this paper. This framework will help in detecting the congestion of traffic on roads. The proposed framework also finds shortest path using Internet of Vehicles (IoV) based ACO technique.