Traffic congestion propagation identification method in smart cities

Abstract

Managing the frequent traffic congestion (traffic jams) of the road networks of large cities is a major challenge for municipal traffic management organizations. In order to manage these situations, it is crucial to understand the processes that lead to congestion and propagation, because the occurrence of a traffic jam does not merely paralyze one street or road, but could spill over onto the whole vicinity (even an entire neighborhood). Solutions can be found in professional literature, but they either oversimplify the problem, or fail to provide a scalable solution. In this article, we describe a new method that not only provides an accurate road network model, but is also a scalable solution for identifying the direction of traffic congestion propagation. Our method was subjected to a detailed performance analysis, which was based on real road network data. According to testing, our method outperforms the ones that have been used to date.