There are more than 7,000 public transit agencies in the U.S. (and many more private agencies), and together, they are responsible for serving 60 billion passenger miles each year. A well-functioning transit system fosters the growth and expansion of businesses, distributes social and economic benefits, and links the capabilities of community members, thereby enhancing what they can accomplish as a society. Since affordable public transit services are the backbones of many communities, this work investigates ways in which Artificial Intelligence (AI) can improve efficiency and increase utilization from the perspective of transit agencies. This book chapter discusses the primary requirements, objectives, and challenges related to the design of AI-driven smart transportation systems. We focus on three major topics. First, we discuss data sources and data. Second, we provide an overview of how AI can aid decision-making with a focus on transportation. Lastly, we discuss computational problems in the transportation domain and AI approaches to these problems.

翻译：美国现有超过7000家公共交通机构（以及更多私营机构），每年共同承担600亿乘客英里的运输服务。高效运作的交通系统能促进商业发展扩张、分配社会经济利益、连接社区成员能力，从而提升整个社会的综合效能。鉴于经济型公共交通服务是许多社区的支柱，本研究从交通机构视角出发，探索人工智能提升运营效率与资源利用率的可行路径。本章节重点论述AI驱动型智能交通系统设计中的核心需求、关键目标及主要挑战。我们聚焦三大主题：首先探讨数据源与数据类型；其次概述人工智能（特别是交通领域）如何辅助决策；最后阐述交通领域的计算问题及相应AI解决方案。