The regulation of Artificial Intelligence (AI) in transportation is an area of growing interest due to its impact on safety, governance, and public acceptance of autonomous systems. This study employs a systematic literature review (SLR) based on the PRISMA 2020 statement, analyzing publications indexed in Scopus and IEEE Xplore from 2015 to 2025. Research questions were structured using the SPICE framework, addressing regulatory trends, approaches adopted in different regions, and key ethical and safety challenges. The findings indicate that AI regulation in transportation does not develop in isolation but rather adapts to pre-existing regulations in the automotive and technology industries. Divergent regulatory approaches were identified in the U.S., the European Union, and China, reflecting different priorities regarding safety, ethics, and human oversight. Additionally, the most critical challenges include algorithm transparency, liability allocation in incidents involving autonomous vehicles, and balancing safety with economic competitiveness. As its main contribution, this study provides a comprehensive analysis of the evolution of AI regulation in transportation and highlights the need to harmonize international standards to ensure the safe and effective adoption of this technology. Further empirical studies are recommended to assess the practical impact of regulations on road safety and public perception of autonomous systems.