mlsanityData to 14 Oct 2026

LangCoop: Collaborative Driving with Language

arXiv 2504.13406 ↗First posted 18 Apr 2025cs.RO cs.AI cs.CLcited by 25

On the map: End-to-end autonomous driving → Cooperative and V2X driving

Abstract (arXiv)

Multi-agent collaboration holds great promise for enhancing the safety, reliability, and mobility of autonomous driving systems by enabling information sharing among multiple connected agents. However, existing multi-agent communication approaches are hindered by limitations of existing communication media, including high bandwidth demands, agent heterogeneity, and information loss. To address these challenges, we introduce LangCoop, a new paradigm for collaborative autonomous driving that leverages natural language as a compact yet expressive medium for inter-agent communication. LangCoop features two key innovations: Mixture Model Modular Chain-of-thought (M3CoT) for structured zero-shot vision-language reasoning and Natural Language Information Packaging (LangPack) for efficiently packaging information into concise, language-based messages. Through extensive experiments conducted in the CARLA simulations, we demonstrate that LangCoop achieves a remarkable 96% reduction in communication bandwidth (< 2KB per message) compared to image-based communication, while maintaining competitive driving performance in the closed-loop evaluation. Our project page and code are at https://xiangbogaobarry.github.io/LangCoop/.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving. Builds on 52 of its 68 references that are in the map. First posted on arXiv 18 Apr 2025.

Builds on

52 of 68 references.

Closest ancestors · 5

Same direction, newest first

  1. 2025V2V-LLM: Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Models14 Feb
  2. 2024Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework19 Sep
  3. 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models17 Aug
  4. 2024Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System15 Apr
  5. 2022COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles4 May

Other references · 47

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2017CARLA: An Open Urban Driving Simulatorcited by 2,449
  5. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 536
  6. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Modelscited by 490
  7. 2023DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Modelcited by 461
  8. 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
  9. 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
  10. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  11. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 231
  12. 2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
35 more
  1. 2019Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Cloudscited by 165
  2. 2019Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensorscited by 110
  3. 2025AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoningcited by 108
  4. 2024OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Drivingcited by 93
  5. 2024An Extensible Framework for Open Heterogeneous Collaborative Perceptioncited by 87
  6. 2023Collaboration Helps Camera Overtake LiDAR in 3D Detectioncited by 81
  7. 2020DSDNet: Deep Structured self-Driving Networkcited by 62
  8. 2022Bridging the Domain Gap for Multi-Agent Perceptioncited by 60
  9. 2023Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Modelscited by 59
  10. 2025STAMP: Scalable Task And Model-agnostic Collaborative Perceptioncited by 44
  11. 2023CORE: Cooperative Reconstruction for Multi-Agent Perceptioncited by 41
  12. 2024Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Drivingcited by 41
  13. 2025On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspectivecited by 41
  14. 2024AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learningcited by 40
  15. 2023Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perceptioncited by 38
  16. 2023Generative AI-driven Semantic Communication Networks: Architecture, Technologies and Applicationscited by 36
  17. 2024AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Drivingcited by 35
  18. 2024Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehiclescited by 33
  19. 2022PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDARcited by 25
  20. 2023Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Predictioncited by 25
  21. 2023Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Studycited by 24
  22. 2020Depth Completion via Inductive Fusion of Planar LIDAR and Monocular Cameracited by 22
  23. 2024CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficcited by 22
  24. 2020CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehiclescited by 16
  25. 2024On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validationcited by 15
  26. 2024Large Language Models for Human-like Autonomous Driving: A Surveycited by 14
  27. 2024Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMscited by 13
  28. 2025V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridorscited by 13
  29. 2025CoCMT: Communication-Efficient Cross-Modal Transformer for Collaborative Perceptioncited by 13
  30. 2024Generalizing End-To-End Autonomous Driving In Real-World Environments Using Zero-Shot LLMscited by 12
  31. 2024Pragmatic Communication in Multi-Agent Collaborative Perceptioncited by 10
  32. 2025SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Drivingcited by 9
  33. 2023We Need to Talk: Identifying and Overcoming Communication-Critical Scenarios for Self-Drivingcited by 8
  34. 2025Generative AI in Transportation Planning: A Surveycited by 8
  35. 2025Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensorscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 14; 2026: 11.

25 papers.

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  1. 2025DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Drivingcited by 134
  2. 2025A Survey on Vision-Language-Action Models for Autonomous Drivingcited by 72
  3. 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 33
  4. 2025V2X-UniPool: Unifying Multimodal Perception and Knowledge Reasoning for Autonomous Drivingcited by 14
  5. 2026DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Drivingcited by 14
  6. 2025Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospectscited by 12
  7. 2025AirV2X: Unified Air-Ground Vehicle-to-Everything Collaborationcited by 11
  8. 2025QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perceptioncited by 11
  9. 2026SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarioscited by 11
  10. 2025Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competitioncited by 9
  11. 2025Generative AI for Autonomous Driving: Frontiers and Opportunitiescited by 7
  12. 2025Automated Vehicles Should be Connected with Natural Languagecited by 5
13 more
  1. 2025SafeCoop: Unravelling Full Stack Safety in Agentic Collaborative Drivingcited by 2
  2. 2026OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Drivingcited by 2
  3. 2025UNCAP: Uncertainty-Guided Neurosymbolic Planning Using Natural Language Communication for Cooperative Autonomous Vehiclescited by 1
  4. 2025Background Fades, Foreground Leads: Curriculum-Guided Background Pruning for Efficient Foreground-Centric Collaborative Perceptioncited by 1
  5. 2026OpenCOOD-Air: Prompting Heterogeneous Ground-Air Collaborative Perception with Spatial Conversion and Offset Predictioncited by 1
  6. 2026Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAscited by 1
  7. 2025Unleashing Hierarchical Reasoning: An LLM-Driven Framework for Training-Free Referring Video Object Segmentationcited by 0
  8. 2026Safety Case Patterns for VLA-based driving systems: Insights from SimLingocited by 0
  9. 2026LACO: Adaptive Latent Communication for Collaborative Drivingcited by 0
  10. 2026Multi-Agent Embodied Autonomous Driving (MAEAD): From V2X Information Exchange to Shared World Modelscited by 0
  11. 2026G-MARK: Grounded Multi-Agent Reasoning for Cooperative Driving via Knowledge Graphscited by 0
  12. 2026VIPS: Vehicle-Infrastructure Cooperative Planning Benchmark via Pseudo-Simulationcited by 0
  13. 2026CoLMIN: LLM-based Multi-Decision Path Negotiation for Cooperative Autonomous Drivingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning
  2. 2026CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models
  3. 2025Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advances
  4. 2026Rethinking Language's Role in Efficient VLA for Autonomous Vehicles: Toward Smarter, Trustworthy Driving
  5. 2023A Language Agent for Autonomous Driving
  6. 2023Vision Language Models in Autonomous Driving: A Survey and Outlook
  7. 2026Roadside-Cooperative Autonomous Driving: From Data Platform to Vision-Language End-to-End Reasoning
  8. 2025AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving