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 last decade has shown an increasing interest on advanced driver assistance systems
(ADAS) based on shared control, where automation is continuously supporting the driver at …

The remarkable progress in algorithms for machine and deep learning have opened the
doors to new opportunities, and some dark possibilities. However, a bright future awaits …

Safe autonomous navigation of microair vehicles in cluttered dynamic environments is
challenging due to the uncertainties arising from robot localization, sensing, and motion …

In shared autonomy, user input is combined with semi-autonomous control to achieve a
common goal. The goal is often unknown ex-ante, so prior work enables agents to infer the …

This paper proposes a two-stage trajectory planning method for self-driving vehicles (SDVs)
in intersection scenarios with uncertain social circumstances while considering other traffic …

Traditional planning and control methods could fail to find a feasible trajectory for an
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …

Agent behavior is arguably the greatest source of uncertainty in trajectory planning for
autonomous vehicles. This problem has motivated significant amounts of work in the …

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 …

Inferring intent from observed behavior has been studied extensively within the frameworks
of Bayesian inverse planning and inverse reinforcement learning. These methods infer a …