Despite significant recent progress in the field of autonomous driving modern methods still
struggle and can incur serious accidents when encountering long-tail unforeseen events …

Vehicle trajectory prediction has increasingly relied on data-driven solutions, but their ability
to scale to different data domains and the impact of larger dataset sizes on their …

Predicting the future motion of surrounding agents is essential for autonomous vehicles
(AVs) to operate safely in dynamic human-robot-mixed environments. Context information …

In recent years, imitation-based driving planners have reported considerable success.
However, due to the absence of a standardized benchmark, the effectiveness of various …

Simulation plays a crucial role in the development of autonomous vehicles (AVs) due to the
potential risks associated with real-world testing. Although significant progress has been …

Bird's-Eye View (BEV) Perception has received increasing attention in recent years as it
provides a concise and unified spatial representation across views and benefits a diverse …

Autonomous driving (AD) endows vehicles with the capability to drive partly or entirely
without human intervention. AD agents generate driving policies based on online perception …

Microscopic traffic simulation plays a crucial role in transportation engineering by providing
insights into individual vehicle behavior and overall traffic flow. However creating a realistic …

Abstract Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D
Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data …

While recent advances in neural radiance field enable realistic digitization for large-scale
scenes the image-capturing process is still time-consuming and labor-intensive. Previous …