Towards AI Urban Planner in the Age of GenAI, LLMs, and Agentic AI

• URL: http://arxiv.org/abs/2507.14730v1
• Date: Sat, 19 Jul 2025 19:40:42 GMT
• Title: Towards AI Urban Planner in the Age of GenAI, LLMs, and Agentic AI
• Authors: Yanjie Fu,
• Abstract summary: Generative AI, large language models, and agentic AI have emerged separately of urban planning.<n>This paper conceptualizes urban planning as a generative AI task, where AI synthesizes land-use configurations under geospatial, social, and human-centric constraints.
• Score: 24.804782152433873
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Generative AI, large language models, and agentic AI have emerged separately of urban planning. However, the convergence between AI and urban planning presents an interesting opportunity towards AI urban planners. This paper conceptualizes urban planning as a generative AI task, where AI synthesizes land-use configurations under geospatial, social, and human-centric constraints. We survey how generative AI approaches, including VAEs, GANs, transformers, and diffusion models, reshape urban design. We further identify critical gaps: 1) limited research on integrating urban theory guidance, 2) limited research of AI urban planning over multiple spatial resolutions or angularities, 3) limited research on augmenting urban design knowledge from data, and 4) limited research on addressing real-world interactions. To address these limitations, we outline future research directions in theory-guided generation, digital twins, and human-machine co-design, calling for a new synthesis of generative intelligence and participatory urbanism.

Related papers

• Generative AI for Autonomous Driving: Frontiers and Opportunities [145.6465312554513]
  This survey delivers a comprehensive synthesis of the emerging role of GenAI across the autonomous driving stack.<n>We begin by distilling the principles and trade-offs of modern generative modeling, encompassing VAEs, GANs, Diffusion Models, and Large Language Models.<n>We categorize practical applications, such as synthetic data generalization, end-to-end driving strategies, high-fidelity digital twin systems, smart transportation networks, and cross-domain transfer to embodied AI.
  arXiv  Detail & Related papers  (2025-05-13T17:59:20Z)
• Generative AI in Transportation Planning: A Survey [41.38132349994159]
  We present the first comprehensive framework for leveraging GenAI in transportation planning.<n>From the transportation planning perspective, we examine the role of GenAI in automating descriptive, predictive, generative, simulation, and explainable tasks.<n>We address critical challenges, including data scarcity, explainability, bias mitigation, and the development of domain-specific evaluation frameworks.
  arXiv  Detail & Related papers  (2025-03-10T10:33:31Z)
• AI Automatons: AI Systems Intended to Imitate Humans [54.19152688545896]
  There is a growing proliferation of AI systems designed to mimic people's behavior, work, abilities, likenesses, or humanness.<n>The research, design, deployment, and availability of such AI systems have prompted growing concerns about a wide range of possible legal, ethical, and other social impacts.
  arXiv  Detail & Related papers  (2025-03-04T03:55:38Z)
• MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility [52.0930915607703]
  Recent advances in Robotics and Embodied AI make public urban spaces no longer exclusive to humans. Micromobility enabled by AI for short-distance travel in public urban spaces plays a crucial component in the future transportation system. We present MetaUrban, a compositional simulation platform for the AI-driven urban micromobility research.
  arXiv  Detail & Related papers  (2024-07-11T17:56:49Z)
• Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI [129.08019405056262]
  Embodied Artificial Intelligence (Embodied AI) is crucial for achieving Artificial Intelligence (AGI) MLMs andWMs have attracted significant attention due to their remarkable perception, interaction, and reasoning capabilities. In this survey, we give a comprehensive exploration of the latest advancements in Embodied AI.
  arXiv  Detail & Related papers  (2024-07-09T14:14:47Z)
• Leveraging Generative AI for Urban Digital Twins: A Scoping Review on the Autonomous Generation of Urban Data, Scenarios, Designs, and 3D City Models for Smart City Advancement [7.334114326621768]
  Generative Artificial Intelligence (AI) models have demonstrated their unique values in data and code generation. The survey starts with the introduction of popular generative AI models with their application areas, followed by a review of the existing urban science applications. Based on the review, this survey discusses potential opportunities and technical strategies that integrate generative AI models into the next-generation urban digital twins.
  arXiv  Detail & Related papers  (2024-05-29T19:23:07Z)
• Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment [32.53845672285722]
  Urban environments, characterized by their complex, multi-layered networks, face significant challenges in the face of rapid urbanization. Recent developments in big data, artificial intelligence, urban computing, and digital twins have laid the groundwork for sophisticated city modeling and simulation. This paper proposes Urban Generative Intelligence (UGI), a novel foundational platform integrating Large Language Models (LLMs) into urban systems.
  arXiv  Detail & Related papers  (2023-12-19T03:12:13Z)
• Understanding Place Identity with Generative AI [2.1441748927508506]
  generative AI models have the potential to capture the collective image of cities that can make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in understanding human perceptions of the built environment.
  arXiv  Detail & Related papers  (2023-06-07T02:32:45Z)
• Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning [27.549492913085597]
  The two fields of urban planning and artificial intelligence arose and developed separately. There is now cross-pollination and increasing interest in both fields to benefit from the advances of the other.
  arXiv  Detail & Related papers  (2023-04-08T02:19:59Z)
• Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning [57.91323079939641]
  We develop a novel human-instructed deep hierarchical generative model to generate optimal urban plans. The first stage is to label the grids of a target area with latent functionalities to discover functional zones. The second stage is to perceive the planning requirements to form urban functionality projections. The third stage is to leverage multi-attentions to model the zone-zone peer dependencies of the functionality projections to generate grid-level land-use configurations.
  arXiv  Detail & Related papers  (2022-12-01T23:06:41Z)
• Automated Urban Planning aware Spatial Hierarchies and Human Instructions [33.06221365923015]
  We propose a novel, deep, human-instructed urban planner based on generative adversarial networks (GANs) GANs build urban functional zones based on information from human instructions and surrounding contexts. We conduct extensive experiments to validate the efficacy of our work.
  arXiv  Detail & Related papers  (2022-09-26T20:37:02Z)
• Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
  It has become an important topic to explore the impact of AI on society from a people-centered perspective. Previous works in citizen science have identified methods of using AI to engage the public in research. This article discusses the challenges of applying AI in Community Citizen Science.
  arXiv  Detail & Related papers  (2021-10-05T12:51:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.