Urban Planning AI

We investigate how AI can collaborate with planners, support plan-making and decision-making, and facilitate responsible planning automation. Our research also examines human–AI interaction and develops governance frameworks for transparent, accountable, and effective Urban Planning AI.

Cityscape at dusk with illuminated highways and buildings, overlaid with digital icons of people connected by lines, symbolizing a network or connectivity in an urban environment.

What We Do

We investigate how artificial intelligence can support planning analysis, plan-making, and decision-making. Our research examines human–AI collaboration, planning automation, generative AI, data-driven planning, and governance frameworks for the responsible use of AI in planning.

What We Are Trying to Achieve

We aim to develop frameworks, methods, and tools that clarify how AI can be integrated into planning practice, what tasks can be supported or automated, and where human judgment and oversight remain essential. Our goal is to support more transparent, accountable, and effective human–AI collaboration in planning.

Featured Research

Aerial view of a suburban neighborhood with rows of houses, cul-de-sacs, curved streets, grassy areas, small ponds, and some undeveloped lots. Trees and open land border the residential area.

Development of a Prototype Land Use Model for Statewide Transportation Planning Activities

A diagram showing layers of map data over a faint map of Florida, with flowcharts above and to the left illustrating data extraction, input, upload, and projections at state and regional network levels.

Florida Model Information eXchange System (MIXS)

A map of Florida with certain counties shaded green to indicate “Micromobility” and others left white labeled “N/A.” Counties highlighted include Escambia, Leon, Duval, St. Johns, Alachua, Orange, Pinellas, Hillsborough, Sarasota, Charlotte, Broward, and Miami-Dade.

Assessment of Modeling Framework for Micromobility

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Selected Publications

Peng, Z.-R., Lu, K.-F., Liu, Y., & Zhai, W. (2024). The pathway of urban planning AI: From planning support to plan-making. Journal of Planning Education and Research, 44(4), 873–885. https://doi.org/10.1177/0739456X231180568

Peng, Z.-R., Lu, K.-F., Liu, Y., Hou, Q., & Zhang, Q. (2026). Symbiotic Planning Theory: The CORE framework for AI-human co-creation in urban planning. Journal of the American Planning Association. https://doi.org/10.1080/01944363.2026.2640038

Peng, Z.-R. (2026). Symbiotic Planning for Urban Futures: A Paradigm for Human-AI Co-Creation. Elsevier.
https://shop.elsevier.com/books/symbiotic-planning-for-urban-futures/peng/978-0-443-45040-2

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