The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …

The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …

In this paper, we propose GOHOME, a method leveraging graph representations of the High
Definition Map and sparse projections to generate a heatmap output representing the future …

Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …

Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential
for safe and efficient operation of connected automated vehicles under complex driving …

Encoding a driving scene into vector representations has been an essential task for
autonomous driving that can benefit downstream tasks eg, trajectory prediction. The driving …

In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework
allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We …

Trajectory prediction has been a crucial task in building a reliable autonomous driving
system by anticipating possible dangers. One key issue is to generate consistent trajectory …

The accurate trajectory prediction of surrounding vehicles is crucial for the sustainability and
safety of connected and autonomous vehicles under mixed traffic streams in the real world …

Integrating trajectory prediction to the decision-making and planning modules of modular
autonomous driving systems is expected to improve the safety and efficiency of self-driving …