Autonomous vehicles interacting with other traffic participants heavily rely on the perception
and prediction of other agents' behaviors to plan safe trajectories. However, as occlusions …

Autonomous vehicles face numerous challenges to ensure safe operation in unpredictable
and hazardous conditions. The autonomous driving environment is characterized by high …

Navigating safely through occlusion scenarios remains challenging for Autonomous
Vehicles (AVs) due to onboard sensors with obstructed Fields of View (FoVs). Integrating …

Robots in complex multi-agent environments should reason about the intentions of observed
and currently unobserved agents. In this paper, we present a new learning-based method …

Driving autonomous vehicles safely through a complex urban environment remains a
difficult task. The sensor limitations, as well as the various occlusions in the urban …

Motion planning for autonomous vehicles remains a challenge in urban road environments
with occlusions. In this study, we present a motion planning framework that prioritizes safety …

Autonomous vehicles face big challenges guaranteeing provable safety during driving. One
of the major problems is the uncertainty arising from the perception of the surrounding …

As the operational domain of autonomous vehicles expands, encountering occlusions
during navigation becomes unavoidable. Most of the existing research on occlusion-aware …

Safely driving through various occlusion scenarios in urban environments, such as bus
stops or crosswalks, is challenging for autonomous vehicles (AVs). Improving the ability to …

Planning a safe trajectory for an ego vehicle through an environment with occluded regions
is a challenging task. Existing methods use some combination of metrics to evaluate a …