Revista internacional de inteligencia de enjambre y computación evolutiva

Abstracto

Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant Colony Optimization for VANETs

Imad Mahgoub and Wilmer Arellano

We present a novel decentralized and infrastructure-less algorithm to alleviate traffic congestions on road networks and to fill the void left by current algorithms which are either static, centralized, or require infrastructure. The algorithm follows an online approach that seeks stochastic user equilibrium and assigns traffic as it evolves in real time, without prior knowledge of the traffic demand or the schedule of the cars that will enter the road network in the future. Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant Colony Optimization for VANETs is a metaheuristic approach that uses reports from other vehicles to update the vehicle’s perceived view of the road network and change route if necessary. To alleviate the broadcast storm spontaneous clusters are created around traffic incidents and a threshold system based on the level of congestion is used to limit the number of incidents to be reported. Simulation results for the algorithm show a great improvement on travel time over routing based on shortest distance.