Traffic Flow Modelling for Pollution Awareness: The TRAFAIR Experience in the City of Zaragoza

Sergio Ilarri, David Sáez, Raquel Trillo-Lado

Abstract

Performing a suitable traffic monitoring is a key issue for a smart city, as it can enable better decision making by both citizens and public administrations. For example, a city council can exploit the collected traffic data for traffic management (e.g., to define suitable traffic policies along the city, such as restricting the circulation of traffic in certain areas). Similarly, citizens could use those data to take appropriate mobility decisions. To measure traffic, a variety of detection methods can be used, but their widespread deployment through the whole city is expensive and difficult to maintain. Therefore, alternative approaches are required, that should allow estimating traffic in any area of the city based only on a few real traffic measurements. In this paper, we describe our approach for traffic flow modelling in the city of Zaragoza, which we are currently applying in the European project “TRAFAIR – Understanding Traffic Flows to Improve Air quality”. The TRAFAIR project aims at the development of a platform to estimate the air quality in different areas of a city, and for this purpose traffic data plays a major role. Specifically, we have adopted an approach that combines historical real traffic measurements with the use of the traffic simulator SUMO on top of real roadmaps of the city and applies a trajectory generation strategy that complements the functionalities of SUMO (e.g., SUMO’s calibrators). An experimental evaluation compares several simulation alternatives and shows the benefits of the chosen approach.

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