The motion planners used in self-driving vehicles need to generate trajectories that are safe,
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …

In order to achieve safe and high-quality decision-making and motion planning, autonomous
vehicles should be able to generate accurate probabilistic predictions for uncertain behavior …

Motion planning for car-like robots is one of the major challenges in automated driving. It
requires to solve a two-point boundary value problem that connects a start and a goal …

Motion planning for autonomous vehicles remains a challenge in urban road environments
with occlusions. In this study, we present a motion planning framework that prioritizes safety …

Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …

Accurately predicting future behaviors of surrounding vehicles is an essential capability for
autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others …

One of the main challenges faced by autonomous vehicles operating in mixed traffic
scenarios pertains to ensuring safe and efficient navigation, particularly adhering to the …

The ability to accurately predict feasible multimodal future trajectories of surrounding traffic
participants is crucial for behavior planning in autonomous vehicles. The Motion …

With the rapid development of artificial intelligence technology, the deep learning method
has been introduced for vehicle trajectory prediction in the internet of vehicles, since it …

Motion prediction of surrounding vehicles is one of the most important tasks handled by a
self-driving vehicle, and represents a critical step in the autonomous system necessary to …