Predicting the Traffic Congestion and Optimal Route in a Smart City Exploiting IoT Devices

Abstract

Monitoring and managing traffic congestion is the most challenging problem for many cities today. It has an effect on the environment and disrupts our everyday lives. As the population expands, the number of roads and cars, creating a slew of issues such as travel time delays, fuel waste, air pollution, and transportation-related issues. On another side, the Internet of Things (IoT) provides different devices and systems to monitor and manage the real-time traffic for smart cities. In this paper, we propose a new approach to avoid traffic congestion and obtain an optimal route for vehicles in the smart city exploiting IoT devices. To do this, we create a map of all possible sources and destinations, secondly and we suggested new parameters to determine the optimal path for the vehicle's traffic. The first phase is to obtain a set of candidate paths for each possible source and destination using Ant Colony Optimization based on the unvaried constraints. The second phase is to obtain the principal path for the vehicle to achieve its destination. The simulation results show that our solution reduces the distance and the time of travel and avoids traffic congestion.