Many studies in the field of robot navigation have focused on environment representation
and localization. The goal of map representation is to summarize spatial information in …

Autonomous driving has shown great potential to reform modern transportation. Yet its
reliability and safety have drawn a lot of attention and concerns. Compared with traditional …

The idea of cooperation has been introduced to self-driving cars about a decade ago with
the aim to reduce the occlusion caused by other users or the scene. More recently, the …

Intersections are difficult to navigate for both human drivers and autonomous vehicles
because several diverse traffic rules must be considered. In addition, current traffic rules are …

Decision-making for urban autonomous driving is challenging due to the stochastic nature of
interactive traffic participants and the complexity of road structures. Although reinforcement …

Autonomous vehicle (AV) is one of the most challenging engineering tasks of our era. High-
Definition (HD) maps are a fundamental tool in the development of AVs, being considered …

Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner,
to mimic human driving. This approach has demonstrated suitable vehicle control when …

In recent years, reachability analysis has gained considerable popularity in motion planning
and safeguarding of automated vehicles (AVs). While existing tools for reachability analysis …

Urban complex scenarios are the most challenging situations in the field of Autonomous
Driving (AD). In that sense, an AD pipeline should be tested in countless environments and …

For the classification of traffic scenes, a description model is necessary that can describe the
scene in a uniform way, independent of its domain. A model to describe a traffic scene in a …