Autonomous vehicles rely on their perception systems to acquire information about their
immediate surroundings. It is necessary to detect the presence of other vehicles …

No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

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 …

Forecasting the motion of surrounding vehicles is a critical ability for an autonomous vehicle
deployed in complex traffic. Motion of all vehicles in a scene is governed by the traffic …

Accurate prediction of others' trajectories is essential for autonomous driving. Trajectory
prediction is challenging because it requires reasoning about agents' past movements …

Temporal prediction is critical for making intelligent and robust decisions in complex
dynamic environments. Motion prediction needs to model the inherently uncertain future …

To safely and efficiently navigate through complex traffic scenarios, autonomous vehicles
need to have the ability to predict the future motion of surrounding vehicles. Multiple …

A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …

Forecasting the future behaviors of dynamic actors is an important task in many robotics
applications such as self-driving. It is extremely challenging as actors have latent intentions …