mlsanityData to 7 Oct 2026

Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving

arXiv 2603.25740 ↗First posted 26 Mar 2026cs.RO cs.AI cs.CVcited by 4

On the map: End-to-end autonomous driving → Imitation-learning end-to-end planners

Abstract (arXiv)

Human driving behavior is inherently personal, which is shaped by long-term habits and influenced by short-term intentions. Individuals differ in how they accelerate, brake, merge, yield, and overtake across diverse situations. However, existing end-to-end autonomous driving systems either optimize for generic objectives or rely on fixed driving modes, lacking the ability to adapt to individual preferences or interpret natural language intent. To address this gap, we propose Drive My Way (DMW), a personalized Vision-Language-Action (VLA) driving framework that aligns with users' long-term driving habits and adapts to real-time user instructions. DMW learns a user embedding from our personalized driving dataset collected across multiple real drivers and conditions the policy on this embedding during planning, while natural language instructions provide additional short-term guidance. Closed-loop evaluation on the Bench2Drive benchmark demonstrates that DMW improves style instruction adaptation, and user studies show that its generated behaviors are recognizable as each driver's own style, highlighting personalization as a key capability for human-centered autonomous driving. Our data and code are available at https://dmw-cvpr.github.io/.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Imitation-learning end-to-end planners, one of 9 directions in End-to-end autonomous driving. Builds on 46 of its 54 references that are in the map. First posted on arXiv 26 Mar 2026.

Builds on

46 of 54 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving30 Jun
  2. 2024From Words to Wheels: Automated Style-Customized Policy Generation for Autonomous Driving18 Sep

Other references · 44

  1. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
  2. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  3. 2023InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Taskscited by 2,534
  4. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  5. 2024Qwen2 Technical Reportcited by 2,076
  6. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,219
  7. 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,033
  8. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Modelscited by 482
  9. 2023GPT-Driver: Learning to Drive with GPTcited by 344
  10. 2025AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuningcited by 252
  11. 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Drivingcited by 250
  12. 2025ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generationcited by 177
32 more
  1. 2023Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Drivingcited by 168
  2. 2025FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Drivingcited by 165
  3. 2025VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstructioncited by 154
  4. 2025SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignmentcited by 149
  5. 2023DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Drivingcited by 142
  6. 2025AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoningcited by 108
  7. 2025A Survey on Vision-Language-Action Models for Autonomous Drivingcited by 72
  8. 2024Embodied Understanding of Driving Scenarioscited by 63
  9. 2025Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Modelscited by 60
  10. 2023Personalized Autonomous Driving with Large Language Models: Field Experimentscited by 46
  11. 2023LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programscited by 45
  12. 2025Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysiscited by 37
  13. 2024LaMMA-P: Generalizable Multi-Agent Long-Horizon Task Allocation and Planning with LM-Driven PDDL Plannercited by 31
  14. 2025IRL-VLA: Training an Vision-Language-Action Policy via Reward World Modelcited by 31
  15. 2025UniOcc: A Unified Benchmark for Occupancy Forecasting and Prediction in Autonomous Drivingcited by 27
  16. 2023MAVERIC: A Data-Driven Approach to Personalized Autonomous Drivingcited by 22
  17. 2024On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validationcited by 15
  18. 2023Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimationcited by 10
  19. 2024Adaptive Prediction Ensemble: Improving Out-of-Distribution Generalization of Motion Forecastingcited by 7
  20. 2024Self-supervised Multi-future Occupancy Forecasting for Autonomous Drivingcited by 7
  21. 2025Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generationcited by 7
  22. 2025Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Drivingcited by 7
  23. 2021Personalized Federated Learning of Driver Prediction Models for Autonomous Drivingcited by 6
  24. 2023Predicting Future Spatiotemporal Occupancy Grids with Semantics for Autonomous Drivingcited by 5
  25. 2025PADriver: Towards Personalized Autonomous Drivingcited by 5
  26. 2025TrajEvo: Trajectory Prediction Heuristics Design via LLM-driven Evolutioncited by 5
  27. 2025Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Drivingcited by 3
  28. 2025AutoFocus-IL: VLM-based Saliency Maps for Data-Efficient Visual Imitation Learning without Extra Human Annotationscited by 3
  29. 2024Investigating Personalized Driving Behaviors in Dilemma Zones: Analysis and Prediction of Stop-or-Go Decisionscited by 2
  30. 2025RDD: Retrieval-Based Demonstration Decomposer for Planner Alignment in Long-Horizon Taskscited by 2
  31. 2026CommCP: Efficient Multi-Agent Coordination via LLM-Based Communication with Conformal Predictioncited by 2
  32. 2026Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teamscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Post-Training in End-to-End Autonomous Drivingcited by 2
  2. 2026PLAN-S: Bridging Planning with Latent Style Dynamics for Autonomous Driving World Modelscited by 0
  3. 2026PersonaDrive: Human-Style Retrieval-Augmented VLA Agents for Closed-Loop Driving Simulationcited by 0
  4. 2026SPVC: Structured and Panoptic Video Fixing for Cross-Dataset Driving Scene Renderingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026STAGE: STyle-controllable Action GEneration for personalized autonomous driving
  2. 2026Driving Like Yourself: A Benchmark for Closed-Loop Personalized End-to-End Autonomous Driving
  3. 2025DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
  4. 2026Vega: Learning to Drive with Natural Language Instructions
  5. 2026VL-DPO: Vision-Language-Guided Finetuning for Preference-Aligned Autonomous Driving
  6. 2024Driving Style Alignment for LLM-powered Driver Agent
  7. 2025DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models
  8. 2025Align2Act: Instruction-Tuned Models for Human-Aligned Autonomous Driving