Intelligent Transportation Systems (ITS) have received increasing attention from both academia and industry due to their ability to integrate technology and expertise to create and provide innovative services, improve safety and mobility, and thus increase the efficiency of existing infrastructure. The appearance of new technologies - such as the Internet of Things (IoT) and cloud computing - has provided opportunities for the development of ITS by revolutionizing the modern world of travel via the use of sensors, applications for mobile devices, and other technological advancements. These sensors and mobile devices can gather local information after deployment, and the collected data is very important in making correct decisions with relation to motor drivers. Cloud computing is an extensive way to allow for knowledge discovery, information sharing, and supported decision making when establishing a large, fully functioning, real-time, accurate, and efficient ITS. This new notion involves some key issues in which traditions are replaced by data analysis requiring manual discrimination and resolution to reach optimal solutions.

The data generated by ITS devices is only of value if it gets subjected to analysis, which brings data analytics and optimization into the picture. The emergence of data science and analytics will also provide new tools, by which transportation systems and services will be managed in the future. Many of the most popular data process techniques, including data mining, machine learning, artificial intelligence, data fusion, and so on, can be used to build the ITS and optimize its performance, and the merging of this multitude of technologies and tools into different domains will have a large impact on future transportation systems.

The aim of this Special Issue is to collect original research and review articles that cover a broad range of topics related to data analysis and optimization in the ITS. Potential research topics might span across data analysis and optimization in IoT, such as sensor networks, vehicular technologies such as V2V and V2I, security mechanisms, and infrastructure-level technologies to support transportation. In addition to terrestrial transportation, submissions on cloud computing, network infrastructure, and network optimization - as well as multimedia concerning the ITS - are also of interest.

Potential topics include but are not limited to the following:

• Data distribution platforms for ITS in IoT
• Data optimization for ITS in IoT
• Online optimization for real time traffic data in IoT
• Spatiotemporal visual analysis for ITS in IoT
• Internet of things and internet of vehicles
• Transportation data mining and exploration
• Advanced driver assistance systems in IoT
• Traffic estimation and prediction systems in IoT
• New paradigms for ITS/Vehicular communication in IoT
• Cloud computing based big data mining in IoT
• Fusion of multisource mobility data in IoT
• Vehicle dynamics and control system in IoT