Smart Transportation

Smart transportation leverages advanced technologies to optimize efficiency, safety, and sustainability within transportation systems. Current research heavily focuses on developing and applying AI, particularly reinforcement learning and deep learning models (like graph neural networks and LSTMs), to improve traffic flow prediction, autonomous vehicle navigation, and the management of diverse transportation modes. This work is driven by the need for real-time data analysis from various sensors (lidar, radar, cameras) and the development of robust, data-driven models to address challenges in areas such as multi-modal sensing, communication, and decision-making. The ultimate goal is to create more efficient, safer, and environmentally friendly transportation networks.