In this review, we provide an overview of emerging trends and challenges in the field of
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …

The state of the art of modelling, control, and optimisation is discussed for automated road
vehicles that may utilise wireless vehicle-to-everything (V2X) connectivity. The appropriate …

Imitation learning has proven to be useful for many real-world problems, but approaches
such as behavioral cloning suffer from data mismatch and compounding error issues. One …

Autonomous driving has been the subject of incre-ased interest in recent years both in
industry and in academia. Serious efforts are being pursued to address legal, technical, and …

Anticipating the future actions of a human is a widely studied problem in robotics that
requires spatio-temporal reasoning. In this work we propose a deep learning approach for …

Abstract Advanced Driver Assistance Systems (ADAS) have made driving safer over the last
decade. They prepare vehicles for unsafe road conditions and alert drivers if they perform a …

This paper highlights the role of humans in the next generation of driver assistance and
intelligent vehicles. Understanding, modeling, and predicting human agents are discussed …

For human drivers, having rear and side-view mirrors is vital for safe driving. They deliver a
more complete view of what is happening around the car. Human drivers also heavily exploit …

Driving requires forecasts. Forecasted movements of objects in the driving scene are
uncertain. Inevitably, decision and control algorithms for autonomous driving need to cope …

High-end vehicles are already equipped with safety systems, such as assistive braking and
automatic lane following, enhancing vehicle safety. Yet, these current solutions can only …