Investigation of Arrival Operational Dynamics and Safety in Point Merge System

The paper addresses the critical issue of enhancing Air Traffic Management efficiency in terminal manoeuvring areas amidst recovering flight traffic intensity. The study focuses on the operational stability of arrival flows, specifically comparing the effectiveness of the innovative Point Merge System (PM) against traditional Radar Vectoring. The research methodology is based on the analysis of large-scale real-world ADS-B trajectory data acquired from the OpenSky Network for Dublin Airport (EIDW). An ETL (Extract, Transform, Load) approach was applied, and a Python-based software suite was developed to calculate Key Performance Indicators, including arrival headway stability, indicated airspeed variability, and trajectory efficiency. The computational experiment results demonstrated that the geometric structure of PM functions as a "passive controller," transforming the stochastic arrival process into a deterministic closed-loop system. It was established that PM implementation reduced velocity variability in the sequencing zone by an average of 12–15 knots, minimizing the "accordion effect" and flight crew workload. Analysis of the Empirical Cumulative Distribution Function (ECDF) for headways revealed a significant reduction in standard deviation, indicating the dissipation of operational entropy. Although the average flight distance within the PM system increased by 12.4%, this is offset by a 60% reduction in holding time. The study concludes that the PM System provides a superior level of predictability and safety margins during peak loads, effectively trading minor distance extensions for enhanced flow stability.