mlsanityData to 7 Oct 2026

Parting with Misconceptions about Learning-based Vehicle Motion Planning

arXiv 2306.07962 ↗First posted 13 Jun 2023cs.RO cs.AI cs.CVcited by 238

Not on the map. Why?

Cited by 160 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The release of nuPlan marks a new era in vehicle motion planning research, offering the first large-scale real-world dataset and evaluation schemes requiring both precise short-term planning and long-horizon ego-forecasting. Existing systems struggle to simultaneously meet both requirements. Indeed, we find that these tasks are fundamentally misaligned and should be addressed independently. We further assess the current state of closed-loop planning in the field, revealing the limitations of learning-based methods in complex real-world scenarios and the value of simple rule-based priors such as centerline selection through lane graph search algorithms. More surprisingly, for the open-loop sub-task, we observe that the best results are achieved when using only this centerline as scene context (i.e., ignoring all information regarding the map and other agents). Combining these insights, we propose an extremely simple and efficient planner which outperforms an extensive set of competitors, winning the nuPlan planning challenge 2023.

Key facts. Cited by 238 papers in the map (data through 7 Oct 2026). Builds on 57 of its 82 references that are in the map. First posted on arXiv 13 Jun 2023.

Builds on

57 of 82 references.

References · 57

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  2. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  3. 2022Planning-oriented Autonomous Drivingcited by 1,068
  4. 2016End to End Learning for Self-Driving Carscited by 1,000
  5. 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclescited by 485
  6. 2017End-to-end Driving via Conditional Imitation Learningcited by 479
  7. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 477
  8. 2018ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worstcited by 391
  9. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  10. 2022ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learningcited by 365
  11. 2019Learning by Cheatingcited by 361
  12. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 343
38 more
  1. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networkscited by 279
  2. 2018Learning to Drive in a Daycited by 266
  3. 2022Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baselinecited by 247
  4. 2021End-to-end Interpretable Neural Motion Plannercited by 240
  5. 2015DeepDriving: Learning Affordance for Direct Perception in Autonomous Drivingcited by 229
  6. 2021MP3: A Unified Model to Map, Perceive, Predict and Plancited by 211
  7. 2021TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviorscited by 192
  8. 2023Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenescited by 191
  9. 2022Guided Conditional Diffusion for Controllable Traffic Simulationcited by 189
  10. 2019PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settingscited by 178
  11. 2021NEAT: Neural Attention Fields for End-to-End Autonomous Drivingcited by 174
  12. 2020Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representationscited by 150
  13. 2016End-to-end Learning of Driving Models from Large-scale Video Datasetscited by 147
  14. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
  15. 2023GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Drivingcited by 141
  16. 2020Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?cited by 139
  17. 2022Learning from All Vehiclescited by 135
  18. 2021Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradientscited by 122
  19. 2021Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversalscited by 112
  20. 2022PlanT: Explainable Planning Transformers via Object-Level Representationscited by 105
  21. 2022TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarioscited by 104
  22. 2018Baidu Apollo EM Motion Plannercited by 99
  23. 2021LookOut: Diverse Multi-Future Prediction and Planning for Self-Drivingcited by 96
  24. 2022KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradientscited by 95
  25. 2020PiP: Planning-informed Trajectory Prediction for Autonomous Drivingcited by 80
  26. 2022BITS: Bi-level Imitation for Traffic Simulationcited by 80
  27. 2019What the Constant Velocity Model Can Teach Us About Pedestrian Motion Predictioncited by 78
  28. 2021SimNet: Learning Reactive Self-driving Simulations from Real-world Observationscited by 77
  29. 2018Deep Imitative Models for Flexible Inference, Planning, and Controlcited by 75
  30. 2022Differentiable Integrated Motion Prediction and Planning with Learnable Cost Function for Autonomous Drivingcited by 71
  31. 2018Conditional Affordance Learning for Driving in Urban Environmentscited by 70
  32. 2021SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policiescited by 68
  33. 2022GoRela: Go Relative for Viewpoint-Invariant Motion Forecastingcited by 68
  34. 2018On Offline Evaluation of Vision-based Driving Modelscited by 62
  35. 2023TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Predictioncited by 56
  36. 2019Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehiclescited by 51
  37. 2023From Prediction to Planning With Goal Conditioned Lane Graph Traversalscited by 45
  38. 2022DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehiclescited by 36

50 most cited of 57 All 57 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 16; 2024: 49; 2025: 83; 2026: 90.

238 papers.

Sort:

By area:

  1. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 527
  2. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  3. 2023GPT-Driver: Learning to Drive with GPTcited by 344
  4. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  5. 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Drivingcited by 250
  6. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  7. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  8. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
  9. 2023A Language Agent for Autonomous Drivingcited by 161
  10. 2025End-to-End Driving with Online Trajectory Evaluation via BEV World Modelcited by 145
  11. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  12. 2025Diffusion-Based Planning for Autonomous Driving with Flexible Guidancecited by 138
38 more
  1. 2023LLM4Drive: A Survey of Large Language Models for Autonomous Drivingcited by 136
  2. 2025Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tailcited by 136
  3. 2024textitS3Gaussian: Self-Supervised Street Gaussians for Autonomous Drivingcited by 105
  4. 2024Towards learning-based planning:The nuPlan benchmark for real-world autonomous drivingcited by 103
  5. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  6. 2024DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mambacited by 87
  7. 2024PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Drivingcited by 84
  8. 2025Robust Autonomy Emerges from Self-Playcited by 64
  9. 2024Embodied Understanding of Driving Scenarioscited by 63
  10. 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 63
  11. 2024NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Drivingcited by 61
  12. 2025A Survey of World Models for Autonomous Drivingcited by 60
  13. 2023LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoningcited by 59
  14. 2024LidarDM: Generative LiDAR Simulation in a Generated Worldcited by 53
  15. 2023DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Drivingcited by 46
  16. 2024Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Followingcited by 41
  17. 2024Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuningcited by 41
  18. 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 41
  19. 2025iPad: Iterative Proposal-centric End-to-End Autonomous Drivingcited by 41
  20. 2024Solving Motion Planning Tasks with a Scalable Generative Modelcited by 40
  21. 2025Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Trainingcited by 39
  22. 2025DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Drivingcited by 39
  23. 2025RAP: 3D Rasterization Augmented End-to-End Planningcited by 39
  24. 2024Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?cited by 38
  25. 2024PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planningcited by 38
  26. 2024Asynchronous Large Language Model Enhanced Planner for Autonomous Drivingcited by 38
  27. 2026Driving on Registerscited by 38
  28. 2023SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversariescited by 36
  29. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  30. 2025VaViM and VaVAM: Autonomous Driving through Video Generative Modelingcited by 34
  31. 2025CaRL: Learning Scalable Planning Policies with Simple Rewardscited by 34
  32. 2025SimScale: Learning to Drive via Real-World Simulation at Scalecited by 34
  33. 2024Producing and Leveraging Online Map Uncertainty in Trajectory Predictioncited by 32
  34. 2025CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Drivingcited by 31
  35. 2025IRL-VLA: Training an Vision-Language-Action Policy via Reward World Modelcited by 31
  36. 2024Hidden Biases of End-to-End Driving Datasetscited by 30
  37. 2023The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Reviewcited by 29
  38. 2024SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Trafficcited by 27

50 most cited of 238 All 238 (JSON)