A Pheromone-based Artificial Intelligence Vehicular Transportation System

The main focus of this thesis serves to develop an Artificial Intelligence Vehicular Transportation System using the notion of pheromone to control traffic conditions. This system is proposed as Pheromone-based Green Transportation System (PGTS). Initially, traffic condition is modelled through the notion of pheromone and congestion is predicted via artificial intelligence solutions. After forecasting congestion, vehicles are probabilistically rerouted to green paths to reduce upstream congestion while traffic lights are coordinated to disseminate downstream traffic. Intuitively, PGTS reduces pollutant emissions significantly. Additionally, PGTS is robust under different non-recurrent events which promotes system practicality.