The testing of vehicular communication technologies, the study of urban mobility patterns, the evaluation of new traffic policies cannot dispense from vehicle mobility simulation. As is often the case, the larger the dataset, the better. Indeed, in recent years, many projects in the fields of mobility or vehicular communication have sought new traffic simulators with extended areas of investigation, possibly covering a whole city and its suburbs. In this spirit, we have modeled an urban traffic simulation in a 600-Km 2 area in and around the Municipality of Turin, leveraging the SUMO tool. This paper aims at reporting in detail the methodology we followed in the creation of this dataset. Our results demonstrate that a complete modeling of such a wide area is possible at the expense of minor simplifications, reaching a very good level of approximation.

Vehicular traffic simulation in the city of Turin from raw data / Rapelli, Marco; Casetti, Claudio; Gagliardi, Giandomenico. - In: IEEE TRANSACTIONS ON MOBILE COMPUTING. - ISSN 1536-1233. - (2021), pp. 1-1. [10.1109/TMC.2021.3075985]

Vehicular traffic simulation in the city of Turin from raw data

Rapelli, Marco;Casetti, Claudio;
2021

Abstract

The testing of vehicular communication technologies, the study of urban mobility patterns, the evaluation of new traffic policies cannot dispense from vehicle mobility simulation. As is often the case, the larger the dataset, the better. Indeed, in recent years, many projects in the fields of mobility or vehicular communication have sought new traffic simulators with extended areas of investigation, possibly covering a whole city and its suburbs. In this spirit, we have modeled an urban traffic simulation in a 600-Km 2 area in and around the Municipality of Turin, leveraging the SUMO tool. This paper aims at reporting in detail the methodology we followed in the creation of this dataset. Our results demonstrate that a complete modeling of such a wide area is possible at the expense of minor simplifications, reaching a very good level of approximation.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2897636