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Bench2Drive On Bench2Drive

Metrics

Driving Score

Results

Performance results of various models on this benchmark

Model Name
Driving Score
Paper TitleRepository
SparseDrive44.54SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
GenAD44.81GenAD: Generative End-to-End Autonomous Driving-
TCP-traj59.90Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
HiP-AD86.77HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder
DiffAD67.92--
UniAD-Base45.81Planning-oriented Autonomous Driving
TCP40.70Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
AD-MLP18.05Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
DiFSD52.02DiFSD: Ego-Centric Fully Sparse Paradigm with Uncertainty Denoising and Iterative Refinement for Efficient End-to-End Self-Driving
TCP-ctrl30.47Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
VAD42.35VAD: Vectorized Scene Representation for Efficient Autonomous Driving
Hydra-NeXt73.86--
UniAD-Tiny40.73Planning-oriented Autonomous Driving
TransFuser++84.21Hidden Biases of End-to-End Driving Models
Drivetransformer-Large63.46DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving-
SimLingo-Base (CarLLaVa)85.94CarLLaVA: Vision language models for camera-only closed-loop driving-
DriveAdapter64.22DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
ThinkTwice62.44Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
TCP-traj w/o distillation49.30Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
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