A Distributed Intelligent Traffic System Using Ant Colony Optimization: A NetLogo Modeling Approach

As vehicle population continues to increase, traffic management and issues related to congestion is an inevitable consequence. The path taken by drivers to arrive at their destination has the tendency of reducing the traffic within the network or increasing it. The choice of path, however, depends on how much traffic information is available to the drivers at the time of deciding the path to take. It is, therefore, the desire of most drivers to have information on the status of traffic on the candidate routes to a destination. A Distributed Intelligent Traffic System (DITS) which uses Ant Colony Optimization(ACO) to solve the traffic problem is presented in this paper. The DITS is implemented in NetLogo and simulated while studying traffic factors such as average travel speed, average waiting time of cars and the number of stopped cars in queue. Ten separate cases of the simulation have been considered for two scenarios of the DITS, one with ACO and the other without ACO. The average speed for the ACO case was found to be higher in all 10 cases and the average waiting time and the number of stopped cars were lower for the ACO case than the case without ACO, which is the preferred result.