Generative urban design: A systematic review on problem formulation, design generation, and decision-making

IF 5 1区 经济学 Q1 ENVIRONMENTAL STUDIES Progress in Planning Pub Date : 2023-07-22 DOI:10.1016/j.progress.2023.100795
Feifeng Jiang , Jun Ma , Christopher John Webster , Alain J.F. Chiaradia , Yulun Zhou , Zhan Zhao , Xiaohu Zhang
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Abstract

Urban design is the process of designing and shaping the physical forms of cities, towns, and suburbs. It involves the arrangement and design of street systems, groups of buildings, public spaces, and landscapes, to make the urban environment performative and sustainable. The typical design process, reliant on manual work and expert experience has unavoidable low efficiency in generating high-performing design solutions due to the involvement of complex social, institutional, and economic contexts and the trade-off between conflicting preferences of different stakeholder groups. Taking advantage of artificial intelligence (AI) and computational capacity, generative urban design (GUD) has been developed as a trending technical direction to narrow the gaps and produce design solutions with high efficiency at early design stages. It uses computer-aided generative methods, such as evolutionary optimization and deep generative models, to efficiently explore complex solution spaces and automatically generate design options that satisfy conflicting objectives and various constraints. GUD experiments have attracted much attention from academia, practitioners, and public authorities in recent years. However, a systematic review of the current stage of GUD research is lacking. This study, therefore, reports on a systematic investigation of the existing literature according to the three key stages in the GUD process: (1) design problem formulation, (2) design option generation, and (3) decision-making. For each stage, current trends, findings, and limitations from GUD studies are examined. Future directions and potential challenges are discussed and presented. The review is highly interdisciplinary and involves articles from urban study, computer science, social science, management, and other fields. It reports what scholars have found in GUD experiments and organizes a diverse and complicated technical agenda into something accessible to all stakeholders. The results and discoveries will serve as a holistic reference for GUD developers and users in both academia and industry and form a baseline for the field of GUD development in the coming years.

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生成性城市设计:对问题制定、设计生成和决策的系统回顾
城市设计是设计和塑造城市、城镇和郊区物质形态的过程。它涉及街道系统、建筑群、公共空间和景观的安排和设计,使城市环境具有可执行性和可持续性。由于涉及复杂的社会、制度和经济背景,以及不同利益相关群体之间相互冲突的偏好之间的权衡,依赖手工作业和专家经验的典型设计流程在生成高效设计方案方面不可避免地存在效率低下的问题。利用人工智能(AI)和计算能力的优势,生成式城市设计(GUD)已发展成为一种趋势性的技术方向,以缩小差距,在早期设计阶段高效率地生成设计方案。它利用进化优化和深度生成模型等计算机辅助生成方法,高效探索复杂的解决方案空间,并自动生成满足冲突目标和各种约束条件的设计方案。近年来,GUD 实验引起了学术界、从业人员和公共机构的广泛关注。然而,对现阶段的 GUD 研究缺乏系统的回顾。因此,本研究按照 GUD 过程中的三个关键阶段:(1)设计问题的提出;(2)设计方案的生成;(3)决策,对现有文献进行了系统的调查。针对每个阶段,研究了 GUD 研究的当前趋势、发现和局限性。还讨论并提出了未来的方向和潜在的挑战。本综述具有高度的跨学科性,涉及城市研究、计算机科学、社会科学、管理学和其他领域的文章。它报告了学者们在 GUD 实验中的发现,并将多样化和复杂的技术议程组织成所有利益相关者都能理解的内容。这些成果和发现将为学术界和产业界的 GUD 开发人员和用户提供全面的参考,并为未来几年的 GUD 开发领域奠定基础。
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来源期刊
CiteScore
10.70
自引率
1.60%
发文量
26
审稿时长
34 days
期刊介绍: Progress in Planning is a multidisciplinary journal of research monographs offering a convenient and rapid outlet for extended papers in the field of spatial and environmental planning. Each issue comprises a single monograph of between 25,000 and 35,000 words. The journal is fully peer reviewed, has a global readership, and has been in publication since 1972.
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