The research explores the realm of Intelligent Transportation and Traffic Management (ITTM), a dynamic field propelled by cutting-edge technologies and data-driven strategies. In the face of escalating urbanization and burgeoning vehicular traffic, conventional transportation networks grapple with congestion and safety concerns. To address these pressing challenges, researchers are pioneering innovative solutions that harness artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and big data analytics. This research offers a comprehensive analysis of ITTM, highlighting intelligent tools and strategies reshaping transportation systems. It begins by outlining fundamental concepts and challenges in traffic management, emphasizing the need for innovative approaches. The research then delves into the components of an intelligent transportation system (ITS), exploring infrastructure, vehicles, and user interactions facilitated by advanced monitoring and communication systems. Crucially, it examines the application of machine learning, deep learning, and optimization algorithms within ITTM, unveiling their potential to optimize transportation networks and streamline traffic management. Ultimately, the research underscores the transformative impact of modern technologies on transportation systems, paving the way for safer, more efficient, and responsive traffic management practices.
