mlsanityData to 7 Oct 2026

AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning

arXiv 2404.06345 ↗First posted 9 Apr 2024cs.AI cs.ROcited by 40

On the map: End-to-end autonomous driving → Large language models for driving

Abstract (arXiv)

Connected and autonomous driving is developing rapidly in recent years. However, current autonomous driving systems, which are primarily based on data-driven approaches, exhibit deficiencies in interpretability, generalization, and continuing learning capabilities. In addition, the single-vehicle autonomous driving systems lack of the ability of collaboration and negotiation with other vehicles, which is crucial for the safety and efficiency of autonomous driving systems. In order to address these issues, we leverage large language models (LLMs) to develop a novel framework, AgentsCoDriver, to enable multiple vehicles to conduct collaborative driving. AgentsCoDriver consists of five modules: observation module, reasoning engine, cognitive memory module, reinforcement reflection module, and communication module. It can accumulate knowledge, lessons, and experiences over time by continuously interacting with the environment, thereby making itself capable of lifelong learning. In addition, by leveraging the communication module, different agents can exchange information and realize negotiation and collaboration in complex traffic environments. Extensive experiments are conducted and show the superiority of AgentsCoDriver.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). Placed in Large language models for driving, one of 9 directions in End-to-end autonomous driving. Builds on 54 of its 68 references that are in the map. First posted on arXiv 9 Apr 2024.

Builds on

54 of 68 references.

Closest ancestors · 8

Same direction, newest first

  1. 2023A Language Agent for Autonomous Driving17 Nov
  2. 2023Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles12 Oct
  3. 2023LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving4 Oct
  4. 2023Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving3 Oct
  5. 2023DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model2 Oct
  6. 2023DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models28 Sep
  7. 2023Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles19 Sep
  8. 2023Drive Like a Human: Rethinking Autonomous Driving with Large Language Models14 Jul

Other references · 46

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  6. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  7. 2023MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Modelscited by 2,689
  8. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  9. 2023A Survey of Large Language Modelscited by 2,537
  10. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  11. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,761
  12. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
34 more
  1. 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
  2. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  3. 2022Automatic Chain of Thought Prompting in Large Language Modelscited by 684
  4. 2023GPT-Driver: Learning to Drive with GPTcited by 344
  5. 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
  6. 2016Safe, Multi-Agent, Reinforcement Learning for Autonomous Drivingcited by 301
  7. 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
  8. 2023Preference Ranking Optimization for Human Alignmentcited by 283
  9. 2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 270
  10. 2023NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenariocited by 258
  11. 2022Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Mapscited by 255
  12. 2023Building Cooperative Embodied Agents Modularly with Large Language Modelscited by 231
  13. 2021Societal Biases in Language Generation: Progress and Challengescited by 201
  14. 2022Fine-tuning language models to find agreement among humans with diverse preferencescited by 189
  15. 2019F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Cloudscited by 171
  16. 2022V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Drivingcited by 157
  17. 2023Fundamental Limitations of Alignment in Large Language Modelscited by 152
  18. 2023Language Prompt for Autonomous Drivingcited by 110
  19. 2023Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Surveycited by 101
  20. 2023Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networkscited by 95
  21. 2023Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunitiescited by 89
  22. 2023Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planningcited by 88
  23. 2023Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object Navigationcited by 74
  24. 2021Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directionscited by 73
  25. 2024AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networkscited by 64
  26. 2019Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learningcited by 53
  27. 2023HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Drivingcited by 48
  28. 2023MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersectionscited by 38
  29. 2021Explainable AI: current status and future directionscited by 32
  30. 2024Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunitiescited by 32
  31. 2023Rethinking Closed-loop Training for Autonomous Drivingcited by 29
  32. 2023Adaptive Communications in Collaborative Perception with Domain Alignment for Autonomous Drivingcited by 19
  33. 2023Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Citiescited by 15
  34. 2023Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Drivingcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 14; 2025: 18; 2026: 8.

40 papers.

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  1. 2024Mobile Edge Intelligence for Large Language Models: A Contemporary Surveycited by 125
  2. 2024SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Modelscited by 60
  3. 2024How Far Are We From AGI: Are LLMs All We Need?cited by 31
  4. 2025HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Modelscited by 30
  5. 2025LangCoop: Collaborative Driving with Languagecited by 25
  6. 2024AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Mergingcited by 22
  7. 2024SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Frameworkcited by 21
  8. 2025Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advancescited by 21
  9. 2024IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengerscited by 20
  10. 2024Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Frameworkcited by 16
  11. 2024Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attentioncited by 14
  12. 2024Language-Driven Policy Distillation for Cooperative Driving in Multi-Agent Reinforcement Learningcited by 13
28 more
  1. 2024CP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perceptioncited by 13
  2. 2025CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Drivingcited by 13
  3. 2025Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoringcited by 10
  4. 2024Position: Foundation Agents as the Paradigm Shift for Decision Makingcited by 9
  5. 2025GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent Detectioncited by 8
  6. 2025State-Aware Perturbation Optimization for Robust Deep Reinforcement Learningcited by 7
  7. 2025Robust Deep Reinforcement Learning in Robotics via Adaptive Gradient-Masked Adversarial Attackscited by 7
  8. 2025CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learningcited by 7
  9. 2024Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Modelscited by 5
  10. 2025Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Modelscited by 5
  11. 2024Leveraging Edge Intelligence and LLMs to Advance 6G-Enabled Internet of Automated Defense Vehiclescited by 3
  12. 2025Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generationcited by 3
  13. 2024Channel-Aware Throughput Maximization for Cooperative Data Fusion in CAVcited by 2
  14. 2025Urban Computing in the Era of Large Language Modelscited by 2
  15. 2025Task-Aware Parameter-Efficient Fine-Tuning of Large Pre-Trained Models at the Edgecited by 2
  16. 2025Opportunistic Collaborative Planning with Large Vision Model Guided Control and Joint Query-Service Optimizationcited by 2
  17. 2025SafeCoop: Unravelling Full Stack Safety in Agentic Collaborative Drivingcited by 2
  18. 2025SFL-LEO: Asynchronous Split-Federated Learning Design for LEO Satellite-Ground Network Frameworkcited by 1
  19. 2025CP-uniGuard: A Unified, Probability-Agnostic, and Adaptive Framework for Malicious Agent Detection and Defense in Multi-Agent Embodied Perception Systemscited by 1
  20. 2026LATS: Large Language Model Assisted Teacher-Student Framework for Multi-Agent Reinforcement Learning in Traffic Signal Controlcited by 1
  21. 2025DP-TRAE: A Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protectioncited by 0
  22. 2026DSP-Reg: Domain-Sensitive Parameter Regularization for Robust Domain Generalizationcited by 0
  23. 2026AnchorDrive: LLM Scenario Rollout with Anchor-Guided Diffusion Regeneration for Safety-Critical Scenario Generationcited by 0
  24. 2026Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Trafficcited by 0
  25. 2026Unified Context Evolution for LLM Agentscited by 0
  26. 2026Beyond Textual Chain-of-Thought: A Survey on Action-Grounded Reasoning in Autonomous Drivingcited by 0
  27. 2026Large Language Models in the Loop: A Stability- and Network-Aware Survey in Networked Control, Cyber-Physical, and Multi-Agent Systemscited by 0
  28. 2026Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving Systemcited by 0

Similar, not cited

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  1. 2024KoMA: Knowledge-driven Multi-agent Framework for Autonomous Driving with Large Language Models
  2. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving
  3. 2023LLM4Drive: A Survey of Large Language Models for Autonomous Driving
  4. 2025Orchestrate, Generate, Reflect: A VLM-Based Multi-Agent Collaboration Framework for Automated Driving Policy Learning
  5. 2023Personalized Autonomous Driving with Large Language Models: Field Experiments
  6. 2025AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving
  7. 2026LACO: Adaptive Latent Communication for Collaborative Driving
  8. 2024CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Traffic