In the digital era, data has become a pivotal asset, advancing technologies such as autonomous driving. Despite this, data trading faces challenges like the absence of robust pricing methods and the lack of trustworthy trading mechanisms. To address these challenges, we introduce a traffic-oriented data trading platform named Data on The Move (DTM), integrating traffic simulation, data trading, and Artificial Intelligent (AI) agents. The DTM platform supports evident-based data value evaluation and AI-based trading mechanisms. Leveraging the common sense capabilities of Large Language Models (LLMs) to assess traffic state and data value, DTM can determine reasonable traffic data pricing through multi-round interaction and simulations. Moreover, DTM provides a pricing method validation by simulating traffic systems, multi-agent interactions, and the heterogeneity and irrational behaviors of individuals in the trading market. Within the DTM platform, entities such as connected vehicles and traffic light controllers could engage in information collecting, data pricing, trading, and decision-making. Simulation results demonstrate that our proposed AI agent-based pricing approach enhances data trading by offering rational prices, as evidenced by the observed improvement in traffic efficiency. This underscores the effectiveness and practical value of DTM, offering new perspectives for the evolution of data markets and smart cities. To the best of our knowledge, this is the first study employing LLMs in data pricing and a pioneering data trading practice in the field of intelligent vehicles and smart cities.

翻译：在数字时代，数据已成为推动自动驾驶等技术进步的关键资产。然而，数据交易仍面临缺乏稳健定价方法和可信交易机制等挑战。为应对这些挑战，我们提出一个名为“移动数据”（DTM）的交通导向数据交易平台，该平台整合了交通仿真、数据交易与人工智能（AI）智能体。DTM平台支持基于证据的数据价值评估和基于AI的交易机制。通过利用大语言模型（LLMs）的常识能力来评估交通状态与数据价值，DTM能够通过多轮交互与仿真确定合理的交通数据定价。此外，DTM通过模拟交通系统、多智能体交互以及交易市场中个体的异质性与非理性行为，提供了一种定价方法验证框架。在DTM平台中，网联车辆、交通信号控制器等实体可参与信息收集、数据定价、交易与决策。仿真结果表明，我们提出的基于AI智能体的定价方法通过提供合理价格优化了数据交易，这体现在观测到的交通效率提升上。这印证了DTM的有效性与实用价值，为数据市场与智慧城市的发展提供了新视角。据我们所知，这是首次在数据定价中应用LLMs的研究，也是智能车辆与智慧城市领域内开创性的数据交易实践。