Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

This research proposes an optimal control-based motion planner with consideration of the
stochasticity of surrounding human-driven vehicles (HVs). The proposed motion planner is …

A haptic driver–vehicle steering interface is introduced that interacts with the driver through
environmentally mediated torque and stiffness changes, thereby communicating the …

End-to-end deep learning approaches have been proven to be efficient in autonomous
driving and robotics. By using deep learning techniques for decision-making, those systems …

A key aspect of Safe Reinforcement Learning (Safe RL) involves estimating the constraint
condition for the next policy, which is crucial for guiding the optimization of safe policy …

Bei der Betrachtung der Entwicklung von Assistenzsystemen, welche in Serienfahrzeuge
integriert werden, zeichnet sich ein Trend hin zur vollständigen Automatisierung der …

This thesis studies critical zones of automated vehicles. The goal is for the automated
vehicle to complete a car-following or lane change maneuver without collision. For instance …

This thesis studies critical zones of automated vehicles. The goal is for the automated
vehicle to complete a car-following or lane change maneuver without collision. For instance …

Vehicle automation is an area where a lot of investments are currently made. Several driving
assistance systems are already in place in many modern vehicles but more and more …

This study proposes a highway driving strategy for autonomous vehicles. First, a model
predictive control (MPC)-based trajectory planner is built based on a kinematic model. A …