With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

Pedestrian trajectory prediction is one of the main concerns of computer vision problems in
the automotive industry, especially in the field of advanced driver assistance systems. The …

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

Automated vehicles rely heavily on data-driven methods, especially for complex urban
environments. Large datasets of real world measurement data in the form of road user …

Learning socially-aware motion representations is at the core of recent advances in multi-
agent problems, such as human motion forecasting and robot navigation in crowds. Despite …

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …

Autonomous vehicle (AV) industry has evolved rapidly during the past decade. Research
and development in each sub-module (perception, state estimation, motion planning etc.) of …

Anticipating the intentions of vulnerable road users (VRUs) such as pedestrians and cyclists
is critical for performing safe and comfortable driving maneuvers. This is the case for human …

Lately, Autonomous vehicles (AV) have been gaining traction globally owing to their huge
social, economic and environmental benefits. However, the rising safety apprehensions for …