摘要
伴随信息环境和数据基础的变化,人工智能在大数据、语音与图像识别和深度学习等方面取得了发展突破,传统的城市设计技术方法也面临着升级迭代的重要契机。本文从系统阐述国内外人工智能与城市设计技术方法的结合模式入手,以城市中广泛存在并能衔接宏观城市尺度与微观建筑尺度的街区尺度为研究对象,通过进化算法、适应性算法和有监督深度学习等人工智能方法,构建了街区三维形态的智能化设计模块,并提出一套较为完整的城市街区三维形态智能化设计技术流程。在此基础上,通过结合特定具体场地,研究了人机交互下从基底搭建、方案生成到人机交互的实践探索,提出了人工智能与设计师交互式的城市设计模式。本文以街区尺度为媒介,试图解决当下人工智能城市设计在不同尺度上的生成逻辑阻塞与内在机理不明的问题,为未来数字化城市设计技术方法的迭代转型以及相关设计辅助系统的开发研究等提供参考与借鉴。
With the changes in the information environment and data foundation, artificial intelligence has made breakthroughs in the development of big data, language image recognition and deep learning. Traditional urban design technology methods are also facing important opportunities for upgrading and iteration. This paper takes the block scale which is widely available in the city as the research object. Through artificial intelligence methods such as evolutionary algorithms, adaptive algorithms and supervised deep learning, an intelligent design module for the three-dimensional shape of the block is constructed. On this basis, by combining specific sites, the practical exploration of human-computer interaction from base construction, plan generation to human-computer interaction is studied and an interactive urban design model of artificial intelligence and designers is proposed. Using the neighborhood scale as the medium, this paper attempts to solve the problems of generation logic blockage and unclear internal mechanism in current artificial intelligence city design at different scales. At the same time, the paper provides references for the iterative transformation of future digital urban design technology methods and the development research of related design assistance systems.
作者
杨俊宴
朱骁
Yang Junyan;Zhu Xiao
出处
《国际城市规划》
CSSCI
CSCD
北大核心
2021年第2期7-15,共9页
Urban Planning International
基金
国家自然科学基金重点项目“基于大数据的城市中心区空间规划理论与关键技术研究”(51838002)。
关键词
人工智能
城市设计
设计方法
街区形态
人机交互
Artificial Intelligence
Urban Design
Design Method
Block Morphology
Human-Computer Interaction
