Analyzing truck operations and patterns in different urban contexts in Italy using GPS data

The widespread availability of GPS (Global Positioning System) data has significantly enhanced the study of truck traffic by enabling detailed analyses of vehicle movement, routing behaviour, and freight patterns. This paper leverages a large dataset of GPS traces collected across Italy to analyse commercial and industrial vehicle operations within the country’s 14 metropolitan areas, by means of a methodology based on machine learning techniques that enables calculation of key behavioural and environmental indicators. Results reveal clear differences between industrial and commercial freight operations in terms of stop duration, route structure, and CO₂ emissions. A more detailed application to Naples highlights spatial and operational freight dynamics within a complex urban setting and showcases the capability of the proposed approach to provide valuable insights for urban freight planning and environmental policy, while demonstrating the utility of GPS big data in large-scale, comparative mobility research.