Internet of Things(IoT) Enabled Intelligent Traffic Control Management System By Hybrid Swarm Intelligence(SI) Algorithm

The congestion of traffic is one of the problem for road transport in the city. This traffic congestion problem affects by population growth and also usage of vehicles that cause inconvenience for people facing problems like air pollution, routing, traffic congestion. The proposed system Internet of Things(IoT) based Intelligent Transport System using Hybridized algorithm with combination of Ant Colony Optimization(ACO) and Particle Swarm Optimization(PSO) algorithm more effective way to solve the traffic control by dynamically adapt as per the volume of the vehicle traffic at circles. ACO chooses best routing path in rush traffic hours for providing an optimal path in a city traffic for short distance. Particle Swarm Optimization(PSO) algorithm is an optimization algorithm to optimize the vehicle velocity, complex traffic management and congestion avoiding solver to avoid accidents, blocking of traffic and save travel time for the intelligent traffic management system in the city. The computation results shows proposed Intelligent Traffic Control Management System using Hybridized Ant Colony and Particle Swarm Optimization(ITCMSHACPSO) algorithm is provided the best optimized features to enhance performance of Quality of Service(QoS), reliability, maximize vehicle count to reach their destination, avoid congestion in a traffic, best path selection for the route, manage velocity compare with other individual algorithms like ACO, PSO.