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这两个领域曾分别兴起与发展。然而，当前二者正相互渗透，且两个领域对借助对方进展实现突破的兴趣日益增长。本文从可持续性、宜居性、经济性、防灾性和环境性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、对话式人工智能以及地理空间与时间机器学习——联系起来，从而系统分析了人工智能如何促进现代城市规划。其中，一个核心问题是自动化土地利用配置，其可表述为：基于周边地理空间数据、人类移动模式、社交媒体信息、环境指标及经济活动，为目标区域生成土地利用方案与建筑配置。最后，我们阐述了人工智能对城市规划的若干影响，并提出了该交叉领域的关键研究方向。