Human trajectory forecasting with multiple socially interacting agents is of critical importance
for autonomous navigation in human environments, eg, for self-driving cars and social …

Motion forecasting is an important component in autonomous driving systems. One of the
most challenging problems in motion forecasting is interactive trajectory prediction, whose …

One of the major challenges for autonomous vehicles in urban environments is to
understand and predict other road users' actions, in particular, pedestrians at the point of …

Motion Prediction (MP) of multiple surroundings agents is a crucial task in arbitrarily complex
environments, from simple robots to Autonomous Driving Stacks (ADS). Current techniques …

Predicting future trajectories of surrounding agents is essential for safety-critical autonomous
driving. Most existing work focuses on predicting marginal trajectories for each agent …

The trajectory prediction is significant for the decision-making of autonomous driving
vehicles. In this paper, we propose a model to predict the trajectories of target agents around …

Forecasting the motion of surrounding traffic is one of the key challenges in the quest to
achieve safe autonomous driving technology. Current state-of-the-art deep forecasting …

Effective understanding of the environment and accurate trajectory prediction of surrounding
dynamic obstacles are indispensable for intelligent mobile systems (like autonomous …

Automated Vehicles (AVs) have been receiving increasing attention as a potential highly
mechanised, intelligent, self-regulating futuristic mode of transport. AVs are predicted to …

To drive safely in complex traffic environments, autonomous vehicles need to make an
accurate prediction of the future trajectories of nearby heterogeneous traffic agents (ie …