Artificial Intelligence, Big Data and the Internet of Things ( IoT ) have been in constant development within various fields of study for their application, especially within Traffic Management Systems and sustainable urban transport, the above was born with the need to reduce, mitigate and control large traffic flows, polluting emissions from vehicles, long travel times and traffic accidents that occur within cities, especially cities in underdeveloped countries, such as the Latin American zone. It is important to generate development strategies that consider a multidimensional and long-term perspective, the success of urban development requires strategic governance and the construction of public projects and the construction of the habitat as a public matter with social inclusion. Coordinated action is needed for environmental protection, territorial planning and public policies. Therefore, the purpose of this research is to analyze the implementation of Artificial Intelligence, Big Data and IoT within Traffic Management systems, specifically, within the Ibero-American zone, likewise, to examine the most effective artificial intelligence technologies and algorithms such as Predictive Models that provide traffic flows helping to have better control within the roads, these use Neural Networks to improve the statistical models used in these models, Machine Learning and Deep Learning among others, which have shown to have positive results in predicting demand and reducing vehicular congestion and accidents within cities and identify the challenges and limitations found in the implementation of these solutions within cities. For the above, a bibliographic review and a bibliometric analysis were carried out, which was performed using the Scopus database, supported by Bibliometrix and VOSviewer for bibliometrics, analyzing information on data, trends and characteristics of research publication, most preferred and productive journals, author, journal and productive countries, thematic evaluation and co-occurrence of words. The results show a low relevance of Ibero-America within the field of study despite having several investigations developed within it. The knowledge obtained in this research will be valuable for young researchers, industry professionals, transport policy makers and government entities in their search to identify solutions to road congestion.