Intelligent Transportation Systems (ITS) are swiftly advancing to tackle the increasing issues of congestion, safety, sustainability, and urban mobility effectiveness. Recent developments in sensing technologies, Artificial Intelligence (AI), the Internet of Things (IoT), edge-cloud computing, 5G/6G connectivity, and collaborative Vehicle-to-Everything (V2X) communication have fostered a new wave of intelligent mobility solutions. This research offers an extensive summary of new ITS advancements, concentrating on real-time traffic analysis, predictive modeling, ecosystems for autonomous and connected vehicles, digital twins in transportation, and systems for data-driven decision support. The document emphasizes that AI-driven perception, integration of multi-modal data, and decentralized computing frameworks greatly enhance traffic prediction precision, lower latency, and improve incident identification. Additionally, the incorporation of sustainable mobility approaches—like electric vehicle (EV) infrastructure enhancement and intelligent public transportation—showcases the transformative effect of ITS on urban settings. The review ends by highlighting ongoing issues, such as interoperability, cybersecurity, data governance, and limitations in large-scale implementation, while suggesting future research paths for achieving fully autonomous, resilient, and energy-efficient smart mobility systems
 

Intelligent Transportation Systems,Smart Mobility,Artificial Intelligence,Internet of Things,Edge Computing