The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …

Autonomous driving is of great interest to industry and academia alike. The use of machine
learning approaches for autonomous driving has long been studied, but mostly in the …

The autonomous vehicle, as an emerging and rapidly growing field, has received extensive
attention for its futuristic driving experiences. Although the fast developing depth sensors …

Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …

Today, and possibly for a long time to come, the full driving task is too complex an activity to
be fully formalized as a sensing-acting robotics system that can be explicitly solved through …

Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …

The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …

Artificial Intelligence (AI) is revolutionizing the modern society. In the automotive industry,
researchers and developers are actively pushing deep learning based approaches for …

Autonomous driving in urban environments requires intelligent systems that are able to deal
with complex and unpredictable scenarios. Traditional modular approaches focus on …