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Overall safety performance of the air traffic management system: Indicators and analysis

Author

Listed:
  • Di Gravio, Giulio
  • Mancini, Maurizio
  • Patriarca, Riccardo
  • Costantino, Francesco

Abstract

Defining means to assess safety performance and delve into their causes is one of the current and future challenges of the ATM sector. Following the experiences of the Aerospace Performance Factor by FAA and EUROCONTROL, this research aims to apply the Analytic Hierarchy Process (AHP) in order to build synthetic and user-friendly safety-related indicators. Through the analysis and combination of the safety events over time (accidents, incidents and issues), this model will pinpoint critical situations and will address the interventions of the decision makers.

Suggested Citation

  • Di Gravio, Giulio & Mancini, Maurizio & Patriarca, Riccardo & Costantino, Francesco, 2015. "Overall safety performance of the air traffic management system: Indicators and analysis," Journal of Air Transport Management, Elsevier, vol. 44, pages 65-69.
    • Handle: RePEc:eee:jaitra:v:44-45:y:2015:i::p:65-69
    DOI: 10.1016/j.jairtraman.2015.02.005
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    Citations

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    Cited by:

    1. Patriarca, Riccardo & Falegnami, Andrea & Costantino, Francesco & Bilotta, Federico, 2018. "Resilience engineering for socio-technical risk analysis: Application in neuro-surgery," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 321-335.
    2. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    3. Hashem Salarzadeh Jenatabadi & Peyman Babashamsi & Datis Khajeheian & Nader Seyyed Amiri, 2016. "Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling," Sustainability, MDPI, vol. 8(11), pages 1-17, November.
    4. Dai, Wei & Quek, Zhi Hao & Low, Kin Huat, 2024. "Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Jiansong Wu & Zhuqiang Hu & Jinyue Chen & Zheng Li, 2018. "Risk Assessment of Underground Subway Stations to Fire Disasters Using Bayesian Network," Sustainability, MDPI, vol. 10(10), pages 1-21, October.
    6. Tolebi Sailauov & Z. W. Zhong, 2017. "Air Traffic Forecasting Using Optimization for Econometric Models," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 3(5), pages 197-203.
    7. Kaya, Gulsum Kubra & Hocaoglu, Mehmet Fatih, 2020. "Semi-quantitative application to the Functional Resonance Analysis Method for supporting safety management in a complex health-care process," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    8. Kaya, Gulsum Kubra & Ozturk, Fatih & Sariguzel, Emine Emel, 2021. "System-based risk analysis in a tram operating system: Integrating Monte Carlo simulation with the functional resonance analysis method," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Patriarca, Riccardo & Simone, Francesco & Di Gravio, Giulio, 2022. "Modelling cyber resilience in a water treatment and distribution system," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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