Transferable and adaptable driving behavior prediction
While autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient, transferable, and …
driving, humans have long mastered the essence of driving with efficient, transferable, and …
Hierarchical adaptable and transferable networks (hatn) for driving behavior prediction
When autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient transferable and …
driving, humans have long mastered the essence of driving with efficient transferable and …
Bat: Behavior-aware human-like trajectory prediction for autonomous driving
The ability to accurately predict the trajectory of surrounding vehicles is a critical hurdle to
overcome on the journey to fully autonomous vehicles. To address this challenge, we …
overcome on the journey to fully autonomous vehicles. To address this challenge, we …
Learning interaction-aware probabilistic driver behavior models from urban scenarios
Human drivers have complex and individual behavior characteristics which describe how
they act in a specific situation. Accurate behavior models are essential for many applications …
they act in a specific situation. Accurate behavior models are essential for many applications …
Human observation-inspired trajectory prediction for autonomous driving in mixed-autonomy traffic environments
In the burgeoning field of autonomous vehicles (AVs), trajectory prediction remains a
formidable challenge, especially in mixed autonomy environments. Traditional approaches …
formidable challenge, especially in mixed autonomy environments. Traditional approaches …
Multi-agent driving behavior prediction across different scenarios with self-supervised domain knowledge
How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …
autonomous driving. It is significant to have the ability to predict surrounding road …
Bevgpt: Generative pre-trained large model for autonomous driving prediction, decision-making, and planning
Prediction, decision-making, and motion planning are essential for autonomous driving. In
most contemporary works, they are considered as individual modules or combined into a …
most contemporary works, they are considered as individual modules or combined into a …
Improving multi-agent trajectory prediction using traffic states on interactive driving scenarios
Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …
intersections, and roundabouts are challenging due to the high density of agents, varying …
Generic prediction architecture considering both rational and irrational driving behaviors
Accurately predicting future behaviors of surrounding vehicles is an essential capability for
autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others …
autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of others …
Diffusion-based environment-aware trajectory prediction
The ability to predict the future trajectories of traffic participants is crucial for the safe and
efficient operation of autonomous vehicles. In this paper, a diffusion-based generative model …
efficient operation of autonomous vehicles. In this paper, a diffusion-based generative model …