A Data-Driven Approach to Analyze Mobility Patterns and the Built Environment: Evidence from Brescia, Catania, and Salerno (Italy)

Rosita De Vincentis, Federico Karagulian, Carlo Liberto (), Marialisa Nigro, Vincenza Rosati and Gaetano Valenti
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Rosita De Vincentis: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Federico Karagulian: ENEA Research Center Casaccia, Via Anguillarese 301, 00123 Rome, Italy
Carlo Liberto: ENEA Research Center Casaccia, Via Anguillarese 301, 00123 Rome, Italy
Marialisa Nigro: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Vincenza Rosati: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Gaetano Valenti: ENEA Research Center Casaccia, Via Anguillarese 301, 00123 Rome, Italy

Sustainability, 2022, vol. 14, issue 21, 1-14

Abstract: Investigating the correlation between urban mobility patterns and the built environment is crucial to support an integrated approach to transportation and land-use planning in modern cities. In this study, we aim to conduct a data-driven analysis of these two interrelated parts of the urban environment through the estimation of a set of metrics to assist city planners in making well-informed strategic decisions. Metrics are computed by aggregating and correlating different types of data sources. Floating Car Data (FCD) are used to compute metrics on mobility demand and traffic patterns. The built environment metrics are mainly derived from population and housing census data, as well as by investigating the topology and the functional classification adopted in the OpenStreetMap Repository to describe the importance and the role of each street in the overall network. Thanks to this set of metrics, accessibility indexes are then estimated to capture and explain the interaction between traffic patterns and the built environment in three Italian cities: Brescia, Catania, and Salerno. The results confirm that the proposed data-driven approach can extract valuable information to support decisions leading to more sustainable urban mobility volumes and patterns. More specifically, the application results show how the physical shape of each city and the related street network characteristics affect the accessibility profiles of different city zones and, consequently, the associated traffic patterns and travel delays. In particular, the combined analysis of city layouts, street network distributions, and floating car profiles suggests that cities such as Brescia, which is characterized by a homogeneously distributed radial street system, exhibit a more balanced spread of activities and efficient mobility behaviors.

Keywords: mobility patterns; built environment; Floating Car Data; OpenStreetMap repository; road network; accessibility (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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