  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.
