Recently, autonomous driving ignited competitions among car makers and technical
corporations. Low-level autonomous vehicles are already commercially available. However …

High automated vehicles rely on the computing system in the car to understand the
environment and make driving decisions. Therefore, computing system design is essential …

Recently, autonomous driving development ignited competition among car makers and
technical corporations. Low-level automation cars are already commercially available. But …

The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

Highly automated driving (HAD) vehicles are complex systems operating in an open context.
Complexity of these systems as well as limitations and insufficiencies in sensing and …

Environment perception is crucial for autonomous vehicle (AV) safety. Most existing AV
perception algorithms have not studied the surrounding environment complexity and failed …

Autonomous vehicles (AVs) employ sophisticated computer systems and algorithms to
perceive the surroundings, localize, plan, and control the vehicle. With several available …

Recent works have proposed end-to-end autonomous vehicle (AV) architectures comprised
of differentiable modules achieving state-of-the-art driving performance. While they provide …

Conventional cameras employed in autonomous vehicle (AV) systems support many
perception tasks, but are challenged by low-light or high dynamic range scenes, adverse …

Autonomous driving is an emerging technology that has developed rapidly over the last
decade. There have been numerous interdisciplinary challenges imposed on the current …