mlsanityData to 14 Oct 2026

MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersections

arXiv 2307.16118 ↗First posted 30 Jul 2023cs.ROcited by 38

On the map: End-to-end autonomous driving → Reinforcement learning for driving

Abstract (arXiv)

Autonomous driving technology is poised to transform transportation systems. However, achieving safe and accurate multi-task decision-making in complex scenarios, such as unsignalized intersections, remains a challenge for autonomous vehicles. This paper presents a novel approach to this issue with the development of a Multi-Task Decision-Making Generative Pre-trained Transformer (MTD-GPT) model. Leveraging the inherent strengths of reinforcement learning (RL) and the sophisticated sequence modeling capabilities of the Generative Pre-trained Transformer (GPT), the MTD-GPT model is designed to simultaneously manage multiple driving tasks, such as left turns, straight-ahead driving, and right turns at unsignalized intersections. We initially train a single-task RL expert model, sample expert data in the environment, and subsequently utilize a mixed multi-task dataset for offline GPT training. This approach abstracts the multi-task decision-making problem in autonomous driving as a sequence modeling task. The MTD-GPT model is trained and evaluated across several decision-making tasks, demonstrating performance that is either superior or comparable to that of state-of-the-art single-task decision-making models.

Key facts. Cited by 38 papers in the map (data through 14 Oct 2026). Placed in Reinforcement learning for driving, one of 9 directions in End-to-end autonomous driving. Builds on 11 of its 27 references that are in the map. First posted on arXiv 30 Jul 2023.

Builds on

11 of 27 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2017Proximal Policy Optimization Algorithmscited by 15,215
  3. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,546
  4. 2021Transformers in Vision: A Surveycited by 1,013
  5. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 644
  6. 2022Online Decision Transformercited by 196
  7. 2020Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehiclescited by 110
  8. 2020Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approachcited by 31
  9. 2022Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learningcited by 11
  10. 2022Multi-task Safe Reinforcement Learning for Navigating Intersections in Dense Trafficcited by 8
  11. 2022Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challengescited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 6; 2024: 13; 2025: 12; 2026: 7.

38 papers.

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  1. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 289
  2. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  3. 2023LLM4Drive: A Survey of Large Language Models for Autonomous Drivingcited by 136
  4. 2024OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Drivingcited by 83
  5. 2025A Survey on Vision-Language-Action Models for Autonomous Drivingcited by 72
  6. 2025Distilling Multi-modal Large Language Models for Autonomous Drivingcited by 46
  7. 2024AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learningcited by 40
  8. 2024Asynchronous Large Language Model Enhanced Planner for Autonomous Drivingcited by 38
  9. 2024Visual Adversarial Attack on Vision-Language Models for Autonomous Drivingcited by 36
  10. 2023Empowering Autonomous Driving with Large Language Models: A Safety Perspectivecited by 34
  11. 2025Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmapcited by 26
  12. 2025Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directionscited by 23
26 more
  1. 2024Hallucination Detection in Foundation Models for Decision-Making: A Flexible Definition and Review of the State of the Artcited by 17
  2. 2024AD-H: Language-guided Autonomous Driving with Hierarchical Agentscited by 15
  3. 2023Applications of Large Scale Foundation Models for Autonomous Drivingcited by 14
  4. 2024Large Language Models for Human-like Autonomous Driving: A Surveycited by 14
  5. 2025TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learningcited by 13
  6. 2023Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awarenesscited by 12
  7. 2024Large Language Models (LLMs) as Traffic Control Systems at Urban Intersections: A New Paradigmcited by 12
  8. 2024DDM-Lag : A Diffusion-based Decision-making Model for Autonomous Vehicles with Lagrangian Safety Enhancementcited by 11
  9. 2026Bench2Drive-VL: Benchmarks for Closed-Loop Autonomous Driving with Vision-Language Modelscited by 10
  10. 2024Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Drivingcited by 8
  11. 2025Bench2ADVLM: A Closed-Loop Benchmark for Vision-language Models in Autonomous Drivingcited by 8
  12. 2024Autonomous Driving at Unsignalized Intersections: A Review of Decision-Making Challenges and Reinforcement Learning-Based Solutionscited by 7
  13. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  14. 2024Leveraging Large Language Models (LLMs) for Traffic Management at Urban Intersections: The Case of Mixed Traffic Scenarioscited by 6
  15. 2026Generative Scenario Rollouts for End-to-End Autonomous Drivingcited by 6
  16. 2025PADriver: Towards Personalized Autonomous Drivingcited by 5
  17. 2025A Knowledge-Driven Diffusion Policy for End-to-End Autonomous Driving Based on Expert Routingcited by 5
  18. 2025Option Discovery Using LLM-guided Semantic Hierarchical Reinforcement Learningcited by 4
  19. 2025SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMscited by 2
  20. 2026CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Drivingcited by 2
  21. 2025VLMs Guided Interpretable Decision Making for Autonomous Drivingcited by 1
  22. 2026Modular Autonomy with Conversational Interaction: An LLM-driven Framework for Decision Making in Autonomous Drivingcited by 1
  23. 2026ReflexDiffusion: Reflection-Enhanced Trajectory Planning for High-lateral-acceleration Scenarios in Autonomous Drivingcited by 1
  24. 2026Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspectivecited by 1
  25. 2025Visual Reasoning at Urban Intersections: FineTuning GPT-4o for Traffic Conflict Detectioncited by 0
  26. 2026A Survey on End-to-End Autonomous Driving Training from the Perspectives of Data, Strategy, and Platformcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024A GPT-based Decision Transformer for Multi-Vehicle Coordination at Unsignalized Intersections ↗
  2. 2021Multi-task UNet architecture for end-to-end autonomous driving
  3. 2024DriveGPT: Scaling Autoregressive Behavior Models for Driving
  4. 2022Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving
  5. 2022State Dropout-Based Curriculum Reinforcement Learning for Self-Driving at Unsignalized Intersections
  6. 2024GPD-1: Generative Pre-training for Driving
  7. 2024Generalizing Cooperative Eco-driving via Multi-residual Task Learning
  8. 2023Parameterized Decision-making with Multi-modal Perception for Autonomous Driving