Newsroom Articles All News Blog Publications TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning Lab2Car: A Versatile Wrapper for Deploying Experimental Planners in Complex Real-World Environments DriveIRL: Drive in Real Life with Inverse Reinforcement Learning Coming In! Communicating Lane Change Intent in Autonomous Vehicles I See You! Design Factors for Supporting Pedestrian-AV Interaction at Crosswalks Safe to Approach: Insights on Autonomous Vehicle Interaction Protocols with First Responders nuReality: A VR environment for research of pedestrian and autonomous vehicle interactions Panoptic nuScenes dataset: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior nuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles Plane & Sample: Maximizing Information about Autonomous Vehicle Performance Using Submodular Optimization Motion Prediction using Trajectory Sets and Self-Driving Domain Knowledge AMVNET: Assertion-based Multi-View Fusion Network for LiDAR Semantic Segmentation Safety of the Intended Driving Behavior Using Rulebooks Load More
Plane & Sample: Maximizing Information about Autonomous Vehicle Performance Using Submodular Optimization
