New Insights from the Analysis of Free Flow Vehicular Traffic in Highways

Abstract

Building vehicular networks in roads and highways is a challenging research topic with a large number of applications ranging from the prevention of traffic jams and car collisions to efficient route planning. Analyzing the distance between vehicles in roads is a key factor in, e.g., designing vehicular networks protocols or planning a supporting infrastructure to improve connectivity. This work proposes a Gaussian-exponential mixture model to characterize the time distance between vehicles in a highway lane, based on measurements collected at different locations in several highways of the city of Madrid. The model arises from the observed behavior that some vehicles travel very close together, like in a burst mode, showing Gaussian inter-arrival times, while other vehicles are isolated, showing exponentially distributed inter-arrival times. The experiments show that such a Gaussian exponential mixture model accurately characterizes inter-vehicle times as observed from real traces.