Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …

Automated Driving Systems (ADS) require extensive evaluation to assure acceptable levels
of safety before they can operate in real-world traffic. Although many tools are available to …

Planning smooth and energy-efficient paths for wheeled mobile robots is a central task for
applications ranging from autonomous driving to service and intralogistic robotics. Over the …

The development of new assessment methods for the performance of automated vehicles is
essential to enable the deployment of automated driving technologies, due to the complex …

Provable safety is one of the most critical challenges in automated driving. The behavior of
numerous traffic participants in a scene cannot be predicted reliably due to complex …

Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS)
like self-driving cars (SDC) because they are more efficient and less dangerous than field …

With the maturation of autonomous driving technology, the use of autonomous vehicles in a
socially acceptable manner has become a growing demand of the public. Human-like …

Ensuring the safety of autonomous vehicles (AV s) in uncertain traffic scenarios is a major
challenge. In this paper, we address the problem of computing the risk that AV s violate a …

Unmanned Aerial Vehicles (UAVs) are getting closer to becoming ubiquitous in everyday
life. Among them, Micro Aerial Vehicles (MAVs) have seen an outburst of attention recently …

Guaranteed state estimation computes the set of possible states of dynamical systems given
the bounds of model uncertainties, disturbances, and noises. For the first time, we evaluate …