DATA-DRIVEN ANALYSIS OF ARRIVAL FLIGHT TRANSIT EFFICIENCY

In the congested terminal maneuvering areas, radar separation is an important standard to maintain air traffic flow and flight safety. To cater for the high volume of arrival traffic, traffic flow guidance strategies (TFGS) are used. However, inefficient use of TFGS can lead to extra flight time, flight delay, fuel burn, and workload. To quantify these inefficiencies, we investigate the separation trend, merge dynamics, and feature extractions. To this end, we use a dynamic paired radar separation method to monitor the flight separation trend within the TMA. The separation trend has embedded air traffic features including TFGS. The trend behaves differently under various traffic conditions. Using the feature extraction method, we summarize flight trajectory features including vectoring, short-track, standard arrival routes, and holding pattern. We then derive the merge dynamics and merge time of the arrival flights. With flight trajectory features and merge dynamics, we couple the TFGS with the radar separation to identify two inefficiencies in the arrival process, namely, contradictory movement and redundant use of TFGS. Using Hong Kong International Airport as an example, our study demonstrated a new approach in the evaluation of arrival operation efficiency.