Enhanced Rerouting Mechanism with Machine Learning for Travel Time and Congestion Reduction

In this paper, a machine-learning based prediction is applied to detect the congested roads to occur in the future, future number of vehicles, future density of the road, etc. Further working with the rerouting strategy, the alternative route can be found for vehicles so that the travel time can be shortened effectively and the traffic congestion can be alleviated greatly. Through simulations, we demonstrate that our proposed mechanism exhibits better performance with more than 10.1% improvement in the average travel time as compared to the closely related mechanisms in the literature.