This chapter discusses the key technical challenges and future directions in the field of FL for smart mobility. It begins by exploring the technical challenges, including data heterogeneity, communication and bandwidth limitations, model scalability and complexity, security and robustness, and energy consumption, all of which hinder the widespread deployment of FL in transportation systems. The chapter then identifies unresolved pain points and highlights emerging paradigms that may overcome these obstacles, such as the integration of FL with blockchain for trust and auditing, 6G communication for ultra-low latency, and edge intelligence for resource-adaptive FL. The concept of digital twins for virtual-physical system integration is discussed as a potential breakthrough for modeling and simulation. Additionally, the chapter introduces large models and adaptive FL approaches that aim to address the challenges of scalability and resource limitations. It also emphasizes the importance of policy, ethics, and standardization, discussing compliance frameworks, algorithm transparency, fairness, and accountability in the context of FL applications. Finally, the chapter offers a vision for sustainable and secure transportation systems, outlining pathways to realize this vision while connecting the themes discussed throughout the book.