How we spend our 24-hour days varies over time, be it by changes in one’s personal life or external forces like modifications to the built environment or government-level restrictions, as was the case during the recent COVID-19 pandemic. TimeUse+ is a novel survey methodology to collect data on Continua

Transport challenges in cities have never been more urgent. Mobility must be rapidly decarbonized and negative externalities of traffic are gaining more attention. On the other side, growing urban populations and economic growth generate ever more traffic.

How much are common machine learning classifiers, such as Random Forest (RF), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) better in forecasting than traditional discrete choice models? To which extent is it worth to sacrifice the improved interpretability of the latter to achieve a higher prediction Continua

In recent years technological innovations in transportation, such as automated vehicles (AVs), mobility-as-a-service, electric and connected vehicles, have been garnering attention. Some advocates liken the emergence of these technologies to a ‘revolution’ in transportation, while critics characterise this as a gross exaggeration. Despite the uncertainties in technological development, Continua