Traffic AI explores how Artificial Intelligence is revolutionizing urban mobility and traffic management. It highlights the shift from reactive to proactive strategies using intelligent traffic signal control, which dynamically adjusts signal timings based on real-time data, and predictive traffic modeling, leveraging machine learning to forecast traffic patterns. These applications promise to alleviate urban congestion, reduce emissions, and improve overall quality of life, offering a glimpse into the smart cities of the future. The book uniquely focuses on practical implementation challenges and opportunities, moving beyond theoretical discussions to address real-world complexities.It begins by introducing fundamental concepts of AI and traffic management, then delves into applications such as adaptive traffic signal control and autonomous vehicle integration. Case studies from around the world showcase successful implementations and lessons learned, culminating in a discussion of future trends and ethical considerations, making it a comprehensive guide for transportation planners, traffic engineers, and policymakers.