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 …

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 …

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 …

Accurately predicting the future motions of surrounding traffic agents is critical for the safety
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …

Many existing autonomous driving paradigms involve a multi-stage discrete pipeline of
tasks. To better predict the control signals and enhance user safety, an end-to-end approach …

In this paper, we present BEVerse, a unified framework for 3D perception and prediction
based on multi-camera systems. Unlike existing studies focusing on the improvement of …

Predicting multiple plausible future trajectories of the nearby vehicles is crucial for the safety
of autonomous driving. Recent motion prediction approaches attempt to achieve such …

We propose a motion forecasting model that exploits a novel structured map representation
as well as actor-map interactions. Instead of encoding vectorized maps as raster images, we …

Driving requires interacting with road agents and predicting their future behaviour in order to
navigate safely. We present FIERY: a probabilistic future prediction model in bird's-eye view …