Vehicle clustering algorithm for sharing information on traffic congestion

Abstract

We present a method for clustering vehicles that are in the same congested traffic flow. Our goal is to provide a mechanism for sharing information between vehicles in the same situation to ease traffic congestion in urban areas. Because the most accurate source of information about the congested traffic flow is the vehicle at the head of the traffic flow, it first needs to be identified. To do so, we adapt a clustering algorithm by trajectory abstraction. By grouping the vehicles that have the same or similar trajectory into the same cluster, the vehicle at the tail of the traffic flow can discover the vehicle at the head of the traffic flow. Moreover, we adapt an abstracted trajectory representation to compensate for the error in GPS information. Simulation results show that the proposed algorithm provides a higher rate of correctness than existing commonly used clustering algorithms.