Autonomous vehicles (AVs) have emerged as a promising technology for enhancing road
safety and mobility. However, designing AVs involves various critical aspects, such as …

The past years have been characterized by an upsurge in opaque automatic decision
support systems, such as Deep Neural Networks (DNNs). Although DNNs have great …

Connected autonomous vehicles (CAVs) are revolutionizing the development of
transportation due to their potential to improve transportation performance in many ways …

Motion prediction systems play a crucial role in enabling autonomous vehicles to navigate
safely and efficiently in complex traffic scenarios. Graph Neural Network (GNN)-based …

Predicting the motion of other road agents enables autonomous vehicles to perform safe
and efficient path planning. This task is very complex, as the behaviour of road agents …

This paper presents the results of real-world testing of human-vehicle interactions with an
autonomous vehicle equipped with internal and external Human Machine Interfaces (HMIs) …

This study explores the complexities of integrating Artificial Intelligence (AI) into Autonomous
Vehicles (AVs), examining the challenges introduced by AI components and the impact on …

This paper addresses the often overlooked issue of fairness in the autonomous driving
domain, particularly in vision-based perception and prediction systems, which play a pivotal …

Newly introduced vehicles come with various added functions, each time utilizing data from
different sensors. One prominent related function is autonomous driving, which is performed …

This paper presents the results of tests of interactions between real humans and simulated
vehicles in a virtual scenario. Human activity is inserted into the virtual world via a virtual …