Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment
Fengli Xu, Jun Zhang, Chen Gao, Jie Feng, Yong Li

TL;DR
This paper introduces Urban Generative Intelligence (UGI), a foundational platform that integrates Large Language Models into urban systems to create embodied agents for city management and simulation, advancing urban intelligence and complexity understanding.
Contribution
It presents a novel platform combining LLMs, city-specific data, and simulation environments to develop embodied agents for urban challenges, bridging technological capabilities and practical urban applications.
Findings
Development of CityGPT, a city-specific foundation model.
Creation of embodied agents for urban tasks.
Open platform enabling diverse urban agent applications.
Abstract
Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the face of rapid urbanization. These challenges, ranging from traffic congestion and pollution to social inequality, call for advanced technological interventions. Recent developments in big data, artificial intelligence, urban computing, and digital twins have laid the groundwork for sophisticated city modeling and simulation. However, a gap persists between these technological capabilities and their practical implementation in addressing urban challenges in an systemic-intelligent way. This paper proposes Urban Generative Intelligence (UGI), a novel foundational platform integrating Large Language Models (LLMs) into urban systems to foster a new paradigm of urban intelligence. UGI leverages CityGPT, a…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · 3D Modeling in Geospatial Applications
