Landing Approach Runway Detection

Landing approach runway detection (LARD) focuses on enabling autonomous aircraft landing systems to reliably identify runways during the approach phase, a critical task for safe and efficient air travel. Current research emphasizes robust methods, including deep learning architectures like convolutional neural networks and LSTMs, to address challenges such as adversarial attacks and the need for high-quality, diverse datasets that accurately reflect real-world conditions. This research is vital for improving the safety and efficiency of autonomous landing systems, impacting both air traffic management and the development of reliable certification standards for such systems. The creation of comprehensive datasets, like the LARD dataset, is a key focus to facilitate further advancements.