Signalized Intersection

Signalized intersections are a critical focus in transportation research, aiming to improve safety and efficiency for all road users. Current research emphasizes developing accurate predictive models, often employing deep learning architectures like convolutional neural networks and generative adversarial networks, to forecast traffic flow, pedestrian behavior, and vehicle trajectories. These models leverage data from various sources, including video, lidar, and V2X communication, to inform real-time decision-making for traffic signal control and autonomous driving systems. Ultimately, advancements in this area promise to reduce accidents, congestion, and emissions, leading to safer and more sustainable transportation networks.