mlsanityData to 7 Oct 2026

Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?

arXiv 2312.03031 ↗First posted 5 Dec 2023cs.CVcited by 242

On the map: End-to-end autonomous driving → End-to-end system architecture

Abstract (arXiv)

End-to-end autonomous driving recently emerged as a promising research direction to target autonomy from a full-stack perspective. Along this line, many of the latest works follow an open-loop evaluation setting on nuScenes to study the planning behavior. In this paper, we delve deeper into the problem by conducting thorough analyses and demystifying more devils in the details. We initially observed that the nuScenes dataset, characterized by relatively simple driving scenarios, leads to an under-utilization of perception information in end-to-end models incorporating ego status, such as the ego vehicle's velocity. These models tend to rely predominantly on the ego vehicle's status for future path planning. Beyond the limitations of the dataset, we also note that current metrics do not comprehensively assess the planning quality, leading to potentially biased conclusions drawn from existing benchmarks. To address this issue, we introduce a new metric to evaluate whether the predicted trajectories adhere to the road. We further propose a simple baseline able to achieve competitive results without relying on perception annotations. Given the current limitations on the benchmark and metrics, we suggest the community reassess relevant prevailing research and be cautious whether the continued pursuit of state-of-the-art would yield convincing and universal conclusions. Code and models are available at urlhttps://github.com/NVlabs/BEV-Planner

Key facts. Cited by 242 papers in the map (data through 7 Oct 2026). Placed in End-to-end system architecture, one of 9 directions in End-to-end autonomous driving. Builds on 38 of its 48 references that are in the map. First posted on arXiv 5 Dec 2023.

Builds on

38 of 48 references.

Closest ancestors · 6

Same direction, newest first

  1. 2023FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving2 Aug
  2. 2023End-to-end Autonomous Driving: Challenges and Frontiers29 Jun
  3. 2023Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes17 May
  4. 2022ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning15 Jul
  5. 2022Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline16 Jun
  6. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Driving19 Apr

Other references · 32

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  4. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  5. 2022Planning-oriented Autonomous Drivingcited by 1,068
  6. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  7. 2016End to End Learning for Self-Driving Carscited by 1,000
  8. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 613
  9. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  10. 2022PETRv2: A Unified Framework for 3D Perception from Multi-Camera Imagescited by 351
  11. 2022BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detectioncited by 340
  12. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 313
20 more
  1. 2022MapTR: Structured Modeling and Learning for Online Vectorized HD Map Constructioncited by 311
  2. 2022BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervisioncited by 302
  3. 2021MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learningcited by 281
  4. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  5. 2021MP3: A Unified Model to Map, Perceive, Predict and Plancited by 211
  6. 2022Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformercited by 211
  7. 2022Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detectioncited by 177
  8. 2023FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformationcited by 162
  9. 2022M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representationcited by 155
  10. 2020Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representationscited by 150
  11. 2023SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videoscited by 149
  12. 2023StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Constructioncited by 143
  13. 2022PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmarkcited by 140
  14. 2020A Survey of End-to-End Driving: Architectures and Training Methodscited by 123
  15. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  16. 2022ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queriescited by 116
  17. 2023FB-BEV: BEV Representation from Forward-Backward View Transformationscited by 98
  18. 2023Sparse4D v2: Recurrent Temporal Fusion with Sparse Modelcited by 92
  19. 2022Differentiable Raycasting for Self-supervised Occupancy Forecastingcited by 83
  20. 2023Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detectioncited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 40; 2025: 105; 2026: 95.

242 papers.

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By area:

  1. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 527
  2. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  3. 2024Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllabilitycited by 337
  4. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
  5. 2025AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuningcited by 252
  6. 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Drivingcited by 250
  7. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  8. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 239
  9. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  10. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 226
  11. 2025ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generationcited by 177
  12. 2025OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Modelcited by 172
38 more
  1. 2025FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Drivingcited by 165
  2. 2024Enhancing End-to-End Autonomous Driving with Latent World Modelcited by 161
  3. 2025OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoningcited by 142
  4. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  5. 2025Diffusion-Based Planning for Autonomous Driving with Flexible Guidancecited by 138
  6. 2025DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Drivingcited by 125
  7. 2024DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representationcited by 123
  8. 2025Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectivescited by 120
  9. 2024textitS3Gaussian: Self-Supervised Street Gaussians for Autonomous Drivingcited by 105
  10. 2024DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Drivingcited by 98
  11. 2024DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformerscited by 96
  12. 2024OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Drivingcited by 93
  13. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  14. 2025DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planningcited by 91
  15. 2025World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Modelcited by 91
  16. 2024ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restorationcited by 89
  17. 2024VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervisioncited by 85
  18. 2025Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Drivingcited by 84
  19. 2025RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learningcited by 76
  20. 2025ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Drivingcited by 66
  21. 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 63
  22. 2025Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Modelscited by 60
  23. 2025WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-tail Scenarioscited by 60
  24. 2025HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generationcited by 56
  25. 2024Making Large Language Models Better Planners with Reasoning-Decision Alignmentcited by 51
  26. 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
  27. 2024SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Drivingcited by 46
  28. 2024Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Drivingcited by 46
  29. 2024End-to-End Autonomous Driving through V2X Cooperationcited by 42
  30. 2025ReSim: Reliable World Simulation for Autonomous Drivingcited by 42
  31. 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 41
  32. 2025iPad: Iterative Proposal-centric End-to-End Autonomous Drivingcited by 41
  33. 2024Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Drivingcited by 40
  34. 2025Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Trainingcited by 39
  35. 2024PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planningcited by 38
  36. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  37. 2024DreamForge: Motion-Aware Autoregressive Video Generation for Multi-View Driving Scenescited by 34
  38. 2024DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulationcited by 34

50 most cited of 242 All 242 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2023End-to-end Autonomous Driving using Deep Learning: A Systematic Review
  2. 2026Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms
  3. 2024Exploring the Causality of End-to-End Autonomous Driving
  4. 2026Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
  5. 2023DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
  6. 2023PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
  7. 2026Addressing the Waypoint-Action Gap in End-to-End Autonomous Driving via Vehicle Motion Models
  8. 2025FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model