Fuzzy multi-criteria evaluation of risk and safety in the point merge system

Daniil Marshalok, Oleksandr Luppo

Abstract


Subject of study. Arrival sequencing and integrated flow management in the Terminal Manoeuvring Area (TMA) using the Point Merge System (PMS), aligned with Arrival Manager tools (AMAN and Extended-AMAN). This paper presents a transparent and robust comparison of alternative PMS configurations under traffic, weather, and surveillance uncertainty, focusing on safety, efficiency, and environmental impact. Purpose. To develop and validate an open fuzzy multi-criteria assessment framework for PMS configurations that combines Multi-Criteria Decision-Making (MCDM) with a rule-based fuzzy inference system to produce a compact, consistent risk index compatible with Safety Management System (SMS) practices and AMAN decision support. Tasks. (1) Define a harmonized set of safety/efficiency/environmental indicators for PMS configurations; (2) construct fuzzy membership functions and aggregation rules; (3) elicit criterion weights via the Fuzzy Best-Worst Method (Fuzzy-BWM) with a consistency check; (4) rank alternatives with Fuzzy-TOPSIS and VIKOR and assess ranking concordance; (5) design a rule-based fuzzy inference engine for an integrated risk index; (6) validate on TMA data with single and parallel PMS under realistic traffic, weather, and surveillance scenarios. Results obtained. A reproducible workflow for data preparation and indicator normalization is proposed. A library of membership functions and a rule base are built for key indicators (merge-point headway stability, additional track-miles, low-altitude level-off time, compliance with separation minima, and controller-workload proxy). Criterion weights estimated by Fuzzy-BWM are stable. PMS-configuration rankings by Fuzzy-TOPSIS/VIKOR are mutually consistent. A rule-based fuzzy system that fuses local metrics is used to construct a single interpretable risk index. Integration with AMAN supports configuration selection/switching in real time. Conclusions. The framework enables transparent and reproducible comparison of PMS configurations in TMA and supports operational decisions to tune schemes to current demand. The “MCDM + rule-based fuzzy system” links local performance metrics to a global risk index governed by explainable rules. Configurations preserving headway stability while reducing low-altitude level-offs simultaneously minimize loss-of-separation risk and controller-workload proxies. Practical guidance is provided for adapting configurations to traffic and weather variability without violating regulatory minima. Scientific novelty. This paper unifies fuzzy normalization of safety/efficiency/environmental indicators for PMS configuration choice, couples Fuzzy-BWM with Fuzzy-TOPSIS/VIKOR and a rule-based fuzzy inference engine to form a consistent risk index ready for AMAN/SMS integration, and demonstrates applicability in both single- and parallel-PMS TMA; ranking concordance and decision interpretability are evidenced for operational use.

Keywords


point merge system; fuzzy logic; multi-criteria selection; flight safety; risk index

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DOI: https://doi.org/10.32620/aktt.2025.5.08