SOTAVerified

NavSim

Data-Driven Non-Reactive Autonomous Vehicle Benchmark.

Evaluates autonomous driving stacks that produce waypoints with a static dataset using the PDM-Score metric. The PDM-score metric performs a pseudo-simulation by rolling out the trajectory and simulating all other actors via log-replay. This results in an open-loop evaluation that correlates with closed-loop performance.

Papers

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Showing 11–20 of 26 papers

TitleStatusHype
Generalized Trajectory Scoring for End-to-end Multimodal PlanningCode3
GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous DrivingCode3
iPad: Iterative Proposal-centric End-to-End Autonomous DrivingCode2
Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop TrainingCode1
0/1 Deep Neural Networks via Block Coordinate Descent—0
Bench2Drive-R: Turning Real World Data into Reactive Closed-Loop Autonomous Driving Benchmark by Generative Model—0
Centaur: Robust End-to-End Autonomous Driving with Test-Time Training—0
DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning—0
DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers—0
Finetuning Generative Trajectory Model with Reinforcement Learning from Human Feedback—0
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