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Artificial Intelligence in urban design: A systematic review
Tianchen Huang1, Xinyue Ye2, Tan Yigitcanlar3
1Department of Landscape Architecture and Urban Planning & Center for Geospatial Sciences, Applications and Technology, Texas A&M University, College Station, TX 77840, USA.
Cities (London, England)
|July 8, 2026
Summary
Artificial Intelligence (AI) transforms urban design by improving efficiency and adaptability in the design phase. Challenges like integration and bias require structured workflows and human-AI collaboration for sustainable cities.
Area of Science:
- Urban Planning and Design
- Computer Science
- Architecture
Background:
- Artificial Intelligence (AI) is increasingly vital in urban design, enhancing efficiency, scalability, and adaptability.
- Conventional urban design workflows are often manual and time-consuming, presenting limitations AI can address.
Purpose of the Study:
- To systematically review AI applications in urban design, focusing on the design generation phase.
- To identify AI's role in data analysis, scheme generation, optimization, and visualization within urban design.
Main Methods:
- Systematic literature review of AI applications in urban design.
- Analysis of AI methodologies for data processing, automated iterations, and visualization.
Main Results:
- AI significantly enhances efficiency in urban design through rapid data processing and automated iterations.
- AI tools offer advanced visualizations, improving the understanding of design schemes.
- Challenges include fragmented integration, incomplete automation, and potential algorithmic bias.
Conclusions:
- Structured AI workflows and effective human-AI collaboration are crucial for overcoming current limitations.
- Developing diverse datasets is essential for equitable and context-sensitive AI-driven urban design.
- AI-enhanced urban design can foster more sustainable, efficient, and resilient cities.