By 2050, almost 70% of the population will live in cities. As the population grows, travel demand increases and this might affect air quality in urban areas. Traffic is among the main sources of pollution within cities. Therefore, monitoring urban traffic means not only identifying congestion and managing accidents but also preventing the impact on air pollution. Urban traffic modeling and analysis is part of the advanced traffic intelligent management technologies that has become a crucial sector for smart cities. Its main purpose is to predict congestion states of a specific urban transport network and propose improvements in the traffic network that might result into a decrease of the travel times, air pollution and fuel consumption. This paper describes the implementation of an urban traffic flow model in the city of Modena based on real traffic sensor data. This is part of a wide European project that aims at studying the correlation among traffic and air pollution, therefore at combining traffic and air pollution simulations for testing various urban scenarios and raising citizen awareness about air quality where necessary.

From Sensors Data to Urban Traffic Flow Analysis / Po, Laura; Rollo, Federica; Bachechi, Chiara; Corni, Alberto. - (2019), pp. 478-485. ((Intervento presentato al convegno IEEE International Smart Cities Conference (ISC2 2019) tenutosi a Casablanca, Marocco nel October 14-17, 2019 [10.1109/ISC246665.2019.9071639].

From Sensors Data to Urban Traffic Flow Analysis

Laura Po
;
Federica Rollo
;
Chiara Bachechi
;
Alberto Corni
2019

Abstract

By 2050, almost 70% of the population will live in cities. As the population grows, travel demand increases and this might affect air quality in urban areas. Traffic is among the main sources of pollution within cities. Therefore, monitoring urban traffic means not only identifying congestion and managing accidents but also preventing the impact on air pollution. Urban traffic modeling and analysis is part of the advanced traffic intelligent management technologies that has become a crucial sector for smart cities. Its main purpose is to predict congestion states of a specific urban transport network and propose improvements in the traffic network that might result into a decrease of the travel times, air pollution and fuel consumption. This paper describes the implementation of an urban traffic flow model in the city of Modena based on real traffic sensor data. This is part of a wide European project that aims at studying the correlation among traffic and air pollution, therefore at combining traffic and air pollution simulations for testing various urban scenarios and raising citizen awareness about air quality where necessary.
IEEE International Smart Cities Conference (ISC2 2019)
Casablanca, Marocco
October 14-17, 2019
478
485
Po, Laura; Rollo, Federica; Bachechi, Chiara; Corni, Alberto
From Sensors Data to Urban Traffic Flow Analysis / Po, Laura; Rollo, Federica; Bachechi, Chiara; Corni, Alberto. - (2019), pp. 478-485. ((Intervento presentato al convegno IEEE International Smart Cities Conference (ISC2 2019) tenutosi a Casablanca, Marocco nel October 14-17, 2019 [10.1109/ISC246665.2019.9071639].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1186046
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