Travel Patterns after the Deutschlandticket: A Combined Tracking and Survey Approach

Analysis of Italian mobility patterns using institutional and networked data

Traditional data sources, such as population censuses, have several limitations, including long update times, huge costs, and measurement bias, which can lead to gaps in understanding population dynamics. The aim of this article is to assess the quality of new technologies and the usefulness of the Web as a source of m...

Empirical Evidence on Platform Passenger Distribution and Dwell-Time Impacts in Urban Rail Networks

This study empirically examines the spatial distribution of passengers on urban rail platforms and its impact on boarding and alighting. It combines two complementary datasets from Vienna: (i) automated passenger counts, which record approximately 4.4 million boarding and alighting movements at 20 stations on the Vienn...

Where and When to Refuel: A Revealed Preferences Approach to Local Gasoline Markets

A Model for Road Transport in France and the UK, 1910–1930

This article introduces a methodology for the creation of historical road transport networks, focussing on France and the UK between 1910 and 1930. We construct the first road networks for both countries in the early twentieth century, the key take‐off period of motoring. We differentiate roads according to quality, wi...

Recovery Dynamics of Passenger, Cruise and Vehicle Traffic in the Port of Split, 2005–2025: A Statistical Analysis

The Port of Split handles more passengers than any other Croatian port, and its published traffic statistics offer a compact case for applying elementary statistical methods to a real transport problem. This study analyses twenty-one years of annual data, from 2005 to 2025, covering total passengers, cruise passengers...

From flows to events: spatiotemporal insights into Bologna’s mobility using mobile networks

This paper conducts extensive exploratory analysis, develops a Z-score anomaly detection method capable of capturing event-driven disruptions, and designs a regression model achieving a regional-scale MAPE around 10% in inbound-flow forecasting.