Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
How should we integrate representations from complementary sensors for autonomous
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
Trace and pace: Controllable pedestrian animation via guided trajectory diffusion
We introduce a method for generating realistic pedestrian trajectories and full-body
animations that can be controlled to meet user-defined goals. We draw on recent advances …
animations that can be controlled to meet user-defined goals. We draw on recent advances …
A survey on safety-critical driving scenario generation—A methodological perspective
Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …
thanks to the advance in machine learning-enabled sensing and decision-making …
Leveraging generative AI for urban digital twins: a sco** review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city …
The digital transformation of modern cities by integrating advanced information,
communication, and computing technologies has marked the epoch of data-driven smart city …
communication, and computing technologies has marked the epoch of data-driven smart city …
Guided conditional diffusion for controllable traffic simulation
Controllable and realistic traffic simulation is critical for develo** and verifying
autonomous vehicles. Typical heuristic-based traffic models offer flexible control to make …
autonomous vehicles. Typical heuristic-based traffic models offer flexible control to make …
Advdo: Realistic adversarial attacks for trajectory prediction
Trajectory prediction is essential for autonomous vehicles (AVs) to plan correct and safe
driving behaviors. While many prior works aim to achieve higher prediction accuracy, few …
driving behaviors. While many prior works aim to achieve higher prediction accuracy, few …
King: Generating safety-critical driving scenarios for robust imitation via kinematics gradients
Simulators offer the possibility of safe, low-cost development of self-driving systems.
However, current driving simulators exhibit naïve behavior models for background traffic …
However, current driving simulators exhibit naïve behavior models for background traffic …
Deepaccident: A motion and accident prediction benchmark for v2x autonomous driving
Safety is the primary priority of autonomous driving. Nevertheless, no published dataset
currently supports the direct and explainable safety evaluation for autonomous driving. In …
currently supports the direct and explainable safety evaluation for autonomous driving. In …
The waymo open sim agents challenge
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 …
software development. In this work, we introduce the Waymo Open Sim Agents Challenge …
Real-time motion prediction via heterogeneous polyline transformer with relative pose encoding
The real-world deployment of an autonomous driving system requires its components to run
on-board and in real-time, including the motion prediction module that predicts the future …
on-board and in real-time, including the motion prediction module that predicts the future …