Methods for accurate prediction of radio signal quality parameters are crucial for
optimization of mobile networks, and a necessity for future autonomous driving solutions …

Machine learning-based data rate prediction is one of the key drivers for anticipatory mobile
networking with applications such as dynamic Radio Access Technology (RAT) selection …

A new set of lane changing rules is introduced with that the model introduced in Vranken et
al.(2021) is able to simulate multi lane heterogeneous traffic where human driven vehicles …

Exploiting big data knowledge on small devices will pave the way for building truly cognitive
Internet of Things (IoT) systems. Although machine learning has led to great advancements …

Vehicular big data is anticipated to become the “new oil” of the automotive industry which
fuels the development of novel crowdsensing-enabled services. However, the tremendous …

The exploitation of vehicles as mobile sensors acts as a catalyst for novel crowdsensing-
based applications such as intelligent traffic control and distributed weather forecast …

Advancements in intelligent vehicles and Intelligent Transport Systems (ITS) have shown
that they are now feasible in both technology and commerce. However, there are still …

The integration of functions into future communication systems that predict crucial Quality of
Service (QoS) parameters is expected to enable many new or enhanced use cases, for …

The provision of reliable connectivity is envisioned as a key enabler for future autonomous
driving. Anticipatory communication techniques have been proposed for proactively …

The possibility of predicting Quality of Service, and particularly data rates, in mobile
networks will enable new applications for future automated and connected mobility, such as …