mlsanityData to 7 Oct 2026

RAD-LAD: Rule and Language Grounded Autonomous Driving in Real-Time

arXiv 2603.28522 ↗First posted 30 Mar 2026cs.RO cs.AI cs.CVcited by 3

On the map: End-to-end autonomous driving → Reasoning VLA and VLM driving policies

Abstract (arXiv)

We present LAD, a real-time language--action planner with an interruptible architecture that produces a motion plan in a single forward pass (~20 Hz) or generates textual reasoning alongside a motion plan (~10 Hz). LAD is fast enough for real-time closed-loop deployment, achieving ~3x lower latency than prior driving language models while setting a new learning-based state of the art on nuPlan Test14-Hard and InterPlan. We also introduce RAD, a rule-based planner designed to address structural limitations of PDM-Closed. RAD achieves state-of-the-art performance among rule-based planners on nuPlan Test14-Hard and InterPlan. Finally, we show that combining RAD and LAD enables hybrid planning that captures the strengths of both approaches. This hybrid system demonstrates that rules and learning provide complementary capabilities: rules support reliable maneuvering, while language enables adaptive and explainable decision-making.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Reasoning VLA and VLM driving policies, one of 9 directions in End-to-end autonomous driving. Builds on 45 of its 52 references that are in the map. First posted on arXiv 30 Mar 2026.

Builds on

45 of 52 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025A Survey on Vision-Language-Action Models for Autonomous Driving30 Jun
  2. 2025AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning16 Jun
  3. 2024EMMA: End-to-End Multimodal Model for Autonomous Driving30 Oct

Other references · 42

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2025Qwen3 Technical Reportcited by 8,195
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  9. 2025Qwen2.5-VL Technical Reportcited by 5,418
  10. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
  11. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  12. 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,037
30 more
  1. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,653
  2. 2022Planning-oriented Autonomous Drivingcited by 1,068
  3. 2016End to End Learning for Self-Driving Carscited by 1,000
  4. 2022Efficiently Scaling Transformer Inferencecited by 529
  5. 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclescited by 485
  6. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Modelscited by 482
  7. 2023DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Modelcited by 455
  8. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  9. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  10. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 267
  11. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  12. 2023Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?cited by 242
  13. 2023Parting with Misconceptions about Learning-based Vehicle Motion Planningcited by 238
  14. 2025Real-Time Execution of Action Chunking Flow Policiescited by 199
  15. 2023Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenescited by 191
  16. 2023GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Drivingcited by 141
  17. 2025Diffusion-Based Planning for Autonomous Driving with Flexible Guidancecited by 138
  18. 2025TurboQuant: Online Vector Quantization with Near-optimal Distortion Ratecited by 116
  19. 2024PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Drivingcited by 84
  20. 2023LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoningcited by 59
  21. 2024Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Drivingcited by 55
  22. 2024D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Modelscited by 39
  23. 2024Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?cited by 38
  24. 2024Asynchronous Large Language Model Enhanced Planner for Autonomous Drivingcited by 38
  25. 2025Much Ado About Noising: Dispelling the Myths of Generative Robotic Controlcited by 35
  26. 2025CaRL: Learning Scalable Planning Policies with Simple Rewardscited by 34
  27. 2024Generalizing Motion Planners with Mixture of Experts for Autonomous Drivingcited by 22
  28. 2025Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modelingcited by 22
  29. 2024ROADWork: A Dataset and Benchmark for Learning to Recognize, Observe, Analyze and Drive Through Work Zonescited by 20
  30. 2025LANGTRAJ: Diffusion Model and Dataset for Language-Conditioned Trajectory Simulationcited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAscited by 1
  2. 2026Dash2Sim: Closed-Loop Driving Simulation from in-the-wild Dashcam Videoscited by 0
  3. 2026Beyond Textual Chain-of-Thought: A Survey on Action-Grounded Reasoning in Autonomous Drivingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024AD-H: Language-guided Autonomous Driving with Hierarchical Agents
  2. 2024DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving
  3. 2025Towards Human-Centric Autonomous Driving: A Fast-Slow Architecture Integrating Large Language Model Guidance with Reinforcement Learning
  4. 2025FASIONAD++ : Integrating High-Level Instruction and Information Bottleneck in FAt-Slow fusION Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback
  5. 2025ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving
  6. 2025Drive-R1: Bridging Reasoning and Planning in VLMs for Autonomous Driving with Reinforcement Learning
  7. 2025LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios
  8. 2025Align2Act: Instruction-Tuned Models for Human-Aligned Autonomous Driving