mlsanityData to 7 Oct 2026

Open-TI: Open Traffic Intelligence with Augmented Language Model

arXiv 2401.00211 ↗First posted 30 Dec 2023cs.AIcited by 38

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Abstract (arXiv)

Transportation has greatly benefited the cities' development in the modern civilization process. Intelligent transportation, leveraging advanced computer algorithms, could further increase people's daily commuting efficiency. However, intelligent transportation, as a cross-discipline, often requires practitioners to comprehend complicated algorithms and obscure neural networks, bringing a challenge for the advanced techniques to be trusted and deployed in practical industries. Recognizing the expressiveness of the pre-trained large language models, especially the potential of being augmented with abilities to understand and execute intricate commands, we introduce Open-TI. Serving as a bridge to mitigate the industry-academic gap, Open-TI is an innovative model targeting the goal of Turing Indistinguishable Traffic Intelligence, it is augmented with the capability to harness external traffic analysis packages based on existing conversations. Marking its distinction, Open-TI is the first method capable of conducting exhaustive traffic analysis from scratch - spanning from map data acquisition to the eventual execution in complex simulations. Besides, Open-TI is able to conduct task-specific embodiment like training and adapting the traffic signal control policies (TSC), explore demand optimizations, etc. Furthermore, we explored the viability of LLMs directly serving as control agents, by understanding the expected intentions from Open-TI, we designed an agent-to-agent communication mode to support Open-TI conveying messages to ChatZero (control agent), and then the control agent would choose from the action space to proceed the execution. We eventually provide the formal implementation structure, and the open-ended design invites further community-driven enhancements.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Builds on 17 of its 61 references that are in the map. First posted on arXiv 30 Dec 2023.

Builds on

17 of 61 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  5. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  6. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  7. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMscited by 574
  8. 2023Augmented Language Models: a Surveycited by 398
  9. 2023GraphGPT: Graph Instruction Tuning for Large Language Modelscited by 223
  10. 2023TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIscited by 184
  11. 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Researchcited by 158
  12. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
5 more
  1. 2019CoLight: Learning Network-level Cooperation for Traffic Signal Controlcited by 133
  2. 2019CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenariocited by 114
  3. 2023TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Modelscited by 45
  4. 2019Diagnosing Reinforcement Learning for Traffic Signal Controlcited by 33
  5. 2022LibSignal: An Open Library for Traffic Signal Controlcited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 15; 2025: 15; 2026: 8.

38 papers.

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  1. 2024ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoningcited by 95
  2. 2025Uncertainty Quantification and Confidence Calibration in Large Language Models: A Surveycited by 93
  3. 2024UrbanGPT: Spatio-Temporal Large Language Modelscited by 81
  4. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  5. 2024LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environmentscited by 31
  6. 2024OpenCity: Open Spatio-Temporal Foundation Models for Traffic Predictioncited by 27
  7. 2025Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmapcited by 26
  8. 2024Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Modelscited by 23
  9. 2024iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvementcited by 23
  10. 2025Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directionscited by 23
  11. 2024LLM Uncertainty Quantification through Directional Entailment Graph and Claim Level Response Augmentationcited by 22
  12. 2024CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficcited by 22
26 more
  1. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  2. 2025Large Language Models for Combinatorial Optimization: A Systematic Reviewcited by 18
  3. 2024BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysiscited by 16
  4. 2025Large Language Models and Their Applications in Roadway Safety and Mobility Enhancement: A Comprehensive Reviewcited by 8
  5. 2024Privacy-preserving Fine-tuning of Large Language Models through Flatnesscited by 6
  6. 2024MalLight: Influence-Aware Coordinated Traffic Signal Control for Traffic Signal Malfunctionscited by 5
  7. 2025Domain-Enhanced Dual-Branch Model for Efficient and Interpretable Accident Anticipationcited by 5
  8. 2026Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decompositioncited by 5
  9. 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applicationscited by 4
  10. 2026Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignmentcited by 4
  11. 2024Beyond Words: Evaluating Large Language Models in Transportation Planningcited by 3
  12. 2025SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimizationcited by 3
  13. 2025TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Controlcited by 3
  14. 2024Enhancing Traffic Prediction with Textual Data Using Large Language Modelscited by 2
  15. 2025Urban Computing in the Era of Large Language Modelscited by 2
  16. 2025A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Controlcited by 2
  17. 2025Real-time Spatial Retrieval Augmented Generation for Urban Environmentscited by 1
  18. 2025GE-Chat: A Graph Enhanced RAG Framework for Evidential Response Generation of LLMscited by 1
  19. 2025Chat2SPaT: A Large Language Model Based Tool for Automating Traffic Signal Control Plan Managementcited by 1
  20. 2026LATS: Large Language Model Assisted Teacher-Student Framework for Multi-Agent Reinforcement Learning in Traffic Signal Controlcited by 1
  21. 2026LLM Agents for Time-Series: A Surveycited by 1
  22. 2024Responsible AI in NLP: GUS-Net Span-Level Bias Detection Dataset and Benchmark for Generalizations, Unfairness, and Stereotypescited by 0
  23. 2026Earth Science Foundation Models: From Perception to Reasoning and Discoverycited by 0
  24. 2026Position: Uncertainty Quantification in LLMs is Just Unsupervised Clusteringcited by 0
  25. 2026Cost-Optimal Foundation Model Deployment Portfolio for Transportation Managementcited by 0
  26. 2026SimSkill: A Self-Evolving LLM Agent for Skill and Knowledge Accumulation in Traffic Simulationcited by 0