A Simple Approach to Describe Traffic Fluxes and Urban Congestion by Attractors’ Method

Abstract

A statistical approach was used to analyze situations of heavy and congested traffic in urban areas, which included both the recognition of particular locations that attract drivers in a multipoint-to-multipoint traffic structure and their classification (attractor’s value) as a function of the number of people visiting them by car in different time ranges. Attractors' distribution density values have been calculated using a Kernel Density Estimation (KDE) function, and they have been combined with nodal and crucial traffic points and traffic density in a "congestion" map. Finally, cross-comparing congestion values with the location of buildings, the road network and the Corine Land Use/Land Cover environmental classification, a “Quality of Life” map has been generated. The authors use this term because the congestion of traffic flows, with all the problems that it entails (such as long travel time, air and acoustic pollution, and so on) is a good indicator of the quality of life, especially in small towns. The findings demonstrate that this type of "off-line" analysis would permit administrators to quickly and cheaply identify areas where traffic noise and jumps have the greatest impact on citizens' quality of life and, as a result, concentrate costly ground measurements and interventions primarily there.