The growth in global traffic volume leads to more and more traffic jams, air pollution, and accidents. Thus, Intelligent Transportation Systems (ITSs) have emerged as an answer to several transportation challenges. The purpose of this study is to conduct a systematic assessment of ITS through statistical methods and analysis. ITS is characterized as a group of sophisticated applications that seek to utilize information and communication technologies to provide transportation and traffic management services. ITS has integrated several technologies, including data collection, communication, data mining, machine learning, artificial intelligence, and database management. By combining these information technologies, ITS has enabled several applications, such as traffic management, fault identification systems, vehicle information and guidance systems, and driver assistance systems. Studies published after 2008 are the most significant for our goal of creating several popular digital libraries. We summarize this study into issues related to ITS and methods employed to address them. Finally, improvements were sought and it was discovered that the combination of several emerging technologies, such as agent-based computing, cloud computing, and VANETS, among others, made ITS extremely effective in solving issues related to transportation in smart cities.