Drawing upon fundamental research in human behavior prediction, recently there has been
a research focus on how to predict driver behaviors. In this paper we review the field of …

The vision of autonomous driving is piecewise becoming reality. Still the problem of
executing the driving task in a safe and comfortable way in all possible environments, for …

Lane-change decision models with enhanced human-likeness are increasingly important as
they are integral in traffic simulations for training autonomous driving algorithms. This work …

Balancing safety and efficiency when planning in crowded scenarios with uncertain
dynamics is challenging where it is imperative to accomplish the robot's mission without …

By knowing what the driver will do next, it is possible to assist drivers only as much as
necessary. Especially in level two safety relevant collision avoidance systems, it is beneficial …

This paper proposes an architecture for integrated decision-making, motion planning, and
control in autonomous highway driving. The approach anticipates, to some degree …

Automated driving within a lane is a fascinating experience already. However, more exiting
but also technically more challenging is to dare the next step of automating tactical behavior …

The objective of this paper is to develop a micro-economic modeling approach for car-
following behaviors that may capture different risk-taking tendencies when dealing with …

The reliable motion prediction of all traffic participants is one of the main challenges for AVs,
especially in urban environments. Indeed, crowded driving scenarios involve strong and …

Motion planning involves decision making among combinatorial maneuver variants in urban
driving. A planner must consider uncertainties and associated risks of the maneuver …