This survey reviews explainability methods for vision-based self-driving systems trained with
behavior cloning. The concept of explainability has several facets and the need for …

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 …

The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …

Explainable AI, in the context of autonomous systems, like self-driving cars, has drawn broad
interests from researchers. Recent studies have found that providing explanations for …

User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …

The remarkable advancements in Deep Learning (DL) algorithms have fueled enthusiasm
for using Artificial Intelligence (AI) technologies in almost every domain; however, the …

Autonomous driving has attracted interest for interpretable action decision models that mimic
human cognition. Existing interpretable autonomous driving models explore static human …

Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …

Automated driving desires better performance on tasks like motion planning and interacting
with pedestrians in mixed-traffic environments. Deep learning algorithms can achieve high …

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