Autonomous vehicles (AVs) have the potential to significantly revolutionize society by
providing a secure and efficient mode of transportation. Recent years have witnessed …

Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor
savings. Over the past few years, the number of simulators for autonomous driving has …

Realistic and diverse simulation scenarios with reactive and feasible agent behaviors can
be used for validation and verification of self-driving system performance without relying on …

Evaluating the performance of autonomous vehicle planning algorithms necessitates
simulating long-tail safety-critical traffic scenarios. However, traditional methods for …

Before implementing Autonomous Vehicles (AVs) in real-world settings, it is imperative to
conduct thorough safety testing. Virtual simulation testing, known for its high fidelity, cost …

Trajectory generation and prediction are two in-terwoven tasks that play important roles in
planner evaluation and decision making for intelligent vehicles. Most existing methods focus …

Diffusion models are promising for joint trajectory prediction and controllable generation in
autonomous driving, but they face challenges of inefficient inference steps and high …

Interactive behavior modeling of multiple agents is an essential challenge in simulation,
especially in scenarios when agents need to avoid collisions and cooperate at the same …

Trajectory generation and trajectory prediction are two critical tasks in autonomous driving,
which generate various trajectories for testing during development and predict the …

Local planning for a differential wheeled robot is designed to generate kinodynamic feasible
actions that guide the robot to a goal position along the navigation path while avoiding …