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 …

Surround-view fisheye cameras are commonly used for near-field sensing in automated
driving. Four fisheye cameras on four sides of the vehicle are sufficient to cover 360° around …

Current end-to-end autonomous driving methods either run a controller based on a planned
trajectory or perform control prediction directly, which have spanned two separately studied …

In this work we are the first to present an offline policy gradient method for learning imitative
policies for complex urban driving from a large corpus of real-world demonstrations. This is …

This article comprehensively reviews the emerging concept of Internet of Intelligent Things
(IoIT), adopting an integrated perspective centred on the areas of embedded systems, edge …

The core task of any autonomous driving system is to transform sensory inputs into driving
commands. In end-to-end driving, this is achieved via a neural network, with one or multiple …

Driving an automobile involves the tasks of observing surroundings, then making a driving
decision based on these observations (steer, brake, coast, etc.). In autonomous driving, all …

Guaranteeing safety of perception-based learning systems is challenging due to the
absence of ground-truth state information unlike in state-aware control scenarios. In this …

Neuromorphic Systems-on-Chip (NSoCs) are becoming heterogeneous by integrating
general-purpose processors (GPPs) and neural processing units (NPUs) on the same SoC …

Deep learning (DL) has become a driving force and has been widely adopted in many
domains and applications with competitive performance. In practice, to solve the nontrivial …