Evolution of Artificial Intelligence in Transportation Engineering

Artificial Intelligence (AI) is employed in various domains, including biology, medicine, economics, business, engineering, and law; it is revolutionizing the transportation sector. AI has been used in transportation for traffic management, control, incident detection, and driverless vehicles. These applications connect at control, decision, and perception layers. Transportation AI helps improve reliability, reduce risk, and enhance efficiency.

Foundations were laid decades ago, but the rise of the Internet and smartphones have helped generate and share rich datasets. AI is advancing in a three-dimensional space defined by three types of actions: perception and environment modeling; decision-making, including choice and optimization; and execution of physical actions. These loops can be defined in parallel. The introduction of intelligent autonomous control, particularly for airborne vehicles, constituted an initial breakthrough. The subsequent explosion of computing power and intelligent optimization represented another critical juncture, enabling enhancements in transportation reliability, safety, and efficiency. Other paradigmatic rupture include the combination of traffic flow theory with graph theory to create predictive analytics and the emergence of cloud and edge computing, which facilitate data storage, sharing, management, and analysis across different transport modes and users.