Predicting multimodal future behavior of traffic participants is essential for robotic vehicles to
make safe decisions. Existing works explore to directly predict future trajectories based on …

Intersections are quite important and complex traffic scenarios, where the future motion of
surrounding vehicles is an indispensable reference factor for the decision-making or path …

Enabling resilient autonomous motion planning requires robust predictions of surrounding
road users' future behavior. In response to this need and the associated challenges, we …

Predicting the trajectories of surrounding vehicles is important to avoid or mitigate collision
with traffic participants. However, due to limited past information and the uncertainty in future …

This paper addresses the problem of long term location prediction for collision avoidance in
Connected Vehicle (CV) environment where more information about the road and traffic data …

Nowadays, autonomous driving cars have become commercially available. However, the
safety of a self-driving car is still a challenging problem that has not been well studied …

Predicting future trajectories of traffic agents in highly interactive environments is an
essential and challenging problem for the safe operation of autonomous driving systems. On …

One of the critical pieces of the self-driving puzzle is understanding the surroundings of a
self-driving vehicle (SDV) and predicting how these surroundings will change in the near …

Vehicle trajectory prediction at intersections is both essential and challenging for
autonomous vehicle navigation. This problem is aggravated when the traffic is …

Making accurate motion prediction of the surrounding traffic agents such as pedestrians,
vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …