Recent advances in trajectory prediction have shown that explicit reasoning about agents'
intent is important to accurately forecast their motion. However, the current research …

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 idea of cooperation has been introduced to self-driving cars about a decade ago with
the aim to reduce the occlusion caused by other users or the scene. More recently, the …

Imitation learning (IL) is a simple and powerful way to use high-quality human driving data,
which can be collected at scale, to produce human-like behavior. However, policies based …

Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …

Development and safety validation of highly automated vehicles increasingly relies on data
and data-driven methods. In processing sensor datasets for environment perception, it is …

Abstract The Interstate-24 MObility Technology Interstate Observation Network (I-24
MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 …

Birds-Eye-View (BEV) perception can naturally represent natural scenes, which is conducive
to multimodal data processing and fusion. BEV data contain rich semantics and integrate the …

Simulation with realistic, interactive agents represents a key task for autonomous vehicle
software development. In this work, we introduce the Waymo Open Sim Agents Challenge …

Abstract We introduce\textit {Nocturne}, a new 2D driving simulator for investigating multi-
agent coordination under partial observability. The focus of Nocturne is to enable research …