A Taxonomy and Survey of Integrating Emerging Technologies to Intelligent Transportation Systems

In recent decades, rapid urbanization and the growing demand for transportation have significantly contributed to increased pollution, traffic congestion, accidents, and longer travel times. To address these challenges, Intelligent Transportation Systems (ITS) have emerged as a transformative solution, integrating communication technologies within transportation infrastructure and vehicles. By leveraging advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), Blockchain, Digital Twins, and Federated Learning, ITS aim to improve mobility, safety and sustainability in urban environments. This work provides a systematic literature review (SLR) by performing a comprehensive analysis of state-of-the-art approaches for the integration of emerging technologies into Intelligent Transportation Systems. We examine and classify these technological approaches based on their practical applications, including traffic prediction, congestion management, route planning, optimization, and real-time multi-modal integration. Furthermore, we evaluate how these technologies are used in specific applications and how effective they are in supporting multi-modal transportation in both simulations and real-world settings. Our findings highlight the potential of using these technologies, while also identify critical challenges, such as data integration, security, scalability, and adoption of human-centered systems. The main contribution of this work is a taxonomy and classification of cutting-edge solutions into a cohesive ITS architecture, enabling adaptable and resilient urban transportation systems. By identifying current research gaps and evaluating practical implementations, we also present insights to the future direction of ITS with a focus on sustainable, user-centric design. For researchers and practitioners seeking to develop next-generation transportation solutions, this survey serves as a valuable reference, bridging theoretical innovations with real-world applicability.