Obtaining Traffic Information by Urban Air Quality Inspection

TL;DR

This paper proposes a fuzzy-based traffic model derived from air quality data in Palermo, aiming to assist urban administrators in pollution management and transportation policy decisions.

Contribution

It introduces a novel fuzzy modeling approach to estimate urban traffic from air quality measurements, validated over two years of data.

Findings

The model accurately reflects traffic-related pollution levels.

Validation shows the model's reliability over a two-year period.

Provides a new tool for urban pollution assessment.

Abstract

The level of air quality in urban centres is affected by emission of several pollutants, mainly coming from the vehicles flowing in their road networks. This is a well known phenomenon that influences the quality of life of people. Despite the deep concern of researchers and technicians, we are far from a total understanding of this phenomenon. On the contrary, the availability of reliable forecasting models would constitute an important tool for administrators in order of assessing suitable actions concerning the transportation policies, public as well private. Referring to the situation of the running fleet and the measured pollutant concentrations concerning the Italian town of Palermo, a data-deduced traffic model is here derived, its truthfulness being justified by a fuzzyfication of the phenomenon. A first validation of the model is supplied by utilising the emissions characteristics and the pollutant concentrations referring to a two years period of time. This work could represent a first attempt in defining a new approach to the problem of the pollution of the urban contexts, in order of providing administrators with a reliable and easier tool.