The two fields of urban planning and artificial intelligence (AI) arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we introduce the importance of urban planning from the sustainability, living, economic, disaster, and environmental perspectives. We review the fundamental concepts of urban planning and relate these concepts to crucial open problems of machine learning, including adversarial learning, generative neural networks, deep encoder-decoder networks, conversational AI, and geospatial and temporal machine learning, thereby assaying how AI can contribute to modern urban planning. Thus, a central problem is automated land-use configuration, which is formulated as the generation of land uses and building configuration for a target area from surrounding geospatial, human mobility, social media, environment, and economic activities. Finally, we delineate some implications of AI for urban planning and propose key research areas at the intersection of both topics.

翻译：城市规划与人工智能（AI）这两个领域曾各自独立兴起与发展。然而，如今两者之间正出现交叉融合，且两个领域都日益关注如何从对方的进展中获益。本文从可持续性、居住、经济、灾害及环境等视角阐述了城市规划的重要性。我们回顾了城市规划的基本概念，并将这些概念与机器学习的关键开放性问题——包括对抗学习、生成式神经网络、深度编码器-解码器网络、对话式AI以及地理空间与时间机器学习——联系起来，从而探讨AI如何为现代城市规划作出贡献。其中，一个核心问题是自动化土地利用配置，该问题被表述为：基于周边地理空间、人类移动性、社交媒体、环境及经济活动数据，为目标区域生成土地利用与建筑配置方案。最后，我们阐述了AI对城市规划的一些潜在影响，并提出了在这两个主题交叉领域的关键研究方向。