Data-driven intelligent transportation systems: A survey

For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system (D²ITS): a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, D²ITS is trending to become a privacy-aware people-centric more intelligent system. In this paper, we provide a survey on the development of D²ITS, discussing the functionality of its key components and some deployment issues associated with D²ITS. Future research directions for the development of D²ITS is also presented.