Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Behaviour prediction function of an autonomous vehicle predicts the future states of the
nearby vehicles based on the current and past observations of the surrounding environment …

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 …

Motion prediction for the leading vehicle is a critical task for connected autonomous
vehicles. It provides a method to model the leading-following vehicle behavior and analysis …

Despite the advancements in the technologies of autonomous driving, it is still challenging to
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …

The advent of in-vehicle networking systems as well as state-of-the-art sensors and
communication technologies have facilitated the collection of large volume and almost real …

We address the problem of forecasting pedestrian and vehicle trajectories in unknown
environments, conditioned on their past motion and scene structure. Trajectory forecasting is …

For autonomous vehicles driving on roads, future trajectories of surrounding traffic agents
(eg, vehicles, bicycles, pedestrians) are essential information. The prediction of future …

Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …

Imitation Learning (IL) is an appealing approach to learn desirable autonomous behavior.
However, directing IL to achieve arbitrary goals is difficult. In contrast, planning-based …