| id |
caadria2023_305 |
| authors |
Deshpande, Rutvik, Vijay Patel, Sayjel, Weijenberg, Camiel, Nisztuk, Maciej, Corcuera, Miriam, Luo, Jianxi and Zhu, Qihao |
| year |
2023 |
| title |
Generative Pre-Trained Transformers for 15-Minute City Design |
| doi |
https://doi.org/10.52842/conf.caadria.2023.1.595
|
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 595–604 |
| summary |
Cities globally are adopting “The 15-Minute City” as an urban response to various crises, including the Covid-19 Pandemic and climate change. However, the challenge of linking location-specific requirements with potential design solutions hinders its effective implementation. To bridge this gap, this paper introduces a novel urban 15 Minute City concept generation tool that applies an artificial intelligence (AI) method called a pre-trained language model (PLM). The PLM model was fine-tuned with structured examples based on 15-Minute City principles. Using a PLM, the tool maps 15-Minute City concepts to a location and project specific prompt, automatically generating neighbourhood design concepts in the form of natural language. |
| keywords |
15-Minute City, neighbourhood design, data-driven design, urban design, natural language generation, Generative Pre-trained Transformer |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (773,190 bytes) |
| references |
Content-type: text/plain
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| last changed |
2023/06/15 23:14 |
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