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 Plus

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, Plus

To slow down the spread of the coronavirus, the population has been instructed to stay at home if possible. This measure consequently has a major impact on our daily mobility behaviour. But who is being affected, and how?

Researchers at the Future Cities Laboratory are using virtual reality (VR) in cycling experiments to reveal users’ cycling behaviour and preferences in different environments. These insights can help planners understand and quantify the impact of infrastructure improvements in setting guidelines and prioritization of new infrastructure.

Agent-based models in transportation model individual travelers and their interaction in the transport system on a micro-level. A natural advantage of agent-based models are flexibility and the ability to model emergent behavior. Work at IVT has produced a new software package, eqasim, that drastically simplifies the design of Plus