Work Zone

Work zones present significant challenges for traffic management and autonomous vehicle navigation, demanding improved safety and efficiency. Current research focuses on developing accurate traffic flow prediction models, incorporating work zone data into these models (e.g., using graph convolutional networks), and enhancing autonomous vehicle perception and navigation capabilities in dynamic work zone environments through datasets like ROADWork and crowdsourced trajectory data. These advancements aim to mitigate traffic congestion, improve worker safety through augmented reality warnings and optimized autonomous vehicle deployment (like ATMA systems), and ultimately reduce accidents and improve overall transportation system performance.