The need for interpretable and accountable intelligent systems grows along with the
prevalence of artificial intelligence (AI) applications used in everyday life. Explainable AI …

Autonomous driving has achieved significant milestones in research and development over
the last decade. There is increasing interest in the field as the deployment of self-operating …

Existing prototypical-based models address the black-box nature of deep learning.
However, they are sub-optimal as they often assume separate prototypes for each class …

Automated vehicles (AVs) are on the edge of being available on the mass market. Research
often focuses on technical aspects of automation, such as computer vision, sensing, or …

The interdisciplinary field of explainable artificial intelligence (XAI) aims to foster human
understanding of black-box machine learning models through explanation-generating …

As more and more forms of AI become prevalent, it becomes increasingly important to
understand how people develop mental models of these systems. In this work we study …

As more people rely on visualization to inform their personal and collective decisions,
researchers have focused on a broader range of audiences, including “novices.” But …

Automated navigation technology has established itself as an integral facet of intelligent
transportation and smart city systems. Several international technological organizations …

This article reports on a study to investigate how the driving behaviour of autonomous
vehicles influences trust and acceptance. Two different designs were presented to two …

Autonomous vehicles are complex systems that may behave in unexpected ways. From the
drivers' perspective, this can cause stress and lower trust and acceptance of autonomous …