AIHCSep 13, 2023

TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models

arXiv:2309.06719v170 citationsh-index: 18Has Code
Originality Synthesis-oriented
AI Analysis

This work addresses traffic management challenges for urban planners and AI researchers, but it is incremental as it combines existing models without introducing a fundamentally new method.

The paper tackles the problem of applying large language models to urban traffic management by integrating ChatGPT with specialized traffic foundation models, resulting in TrafficGPT, which enhances decision support, task deconstruction, and interactive feedback for traffic control.

With the promotion of chatgpt to the public, Large language models indeed showcase remarkable common sense, reasoning, and planning skills, frequently providing insightful guidance. These capabilities hold significant promise for their application in urban traffic management and control. However, LLMs struggle with addressing traffic issues, especially processing numerical data and interacting with simulations, limiting their potential in solving traffic-related challenges. In parallel, specialized traffic foundation models exist but are typically designed for specific tasks with limited input-output interactions. Combining these models with LLMs presents an opportunity to enhance their capacity for tackling complex traffic-related problems and providing insightful suggestions. To bridge this gap, we present TrafficGPT, a fusion of ChatGPT and traffic foundation models. This integration yields the following key enhancements: 1) empowering ChatGPT with the capacity to view, analyze, process traffic data, and provide insightful decision support for urban transportation system management; 2) facilitating the intelligent deconstruction of broad and complex tasks and sequential utilization of traffic foundation models for their gradual completion; 3) aiding human decision-making in traffic control through natural language dialogues; and 4) enabling interactive feedback and solicitation of revised outcomes. By seamlessly intertwining large language model and traffic expertise, TrafficGPT not only advances traffic management but also offers a novel approach to leveraging AI capabilities in this domain. The TrafficGPT demo can be found in https://github.com/lijlansg/TrafficGPT.git.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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