IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v244y2024ics0951832023008220.html
   My bibliography  Save this article

Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations

Author

Listed:
  • Dai, Wei
  • Quek, Zhi Hao
  • Low, Kin Huat

Abstract

This study targets the scenario where centralized tracking systems provide tactical conflict detection for urban air mobility (UAM) flights. In this scenario, the interaction between airspace design and tracking system performances, and its impact on the effectiveness of conflict detection have not been addressed in the literature. To overcome this gap, this study aims at achieving probabilistic modeling and reasoning analysis, to provide references for stakeholders in the design of urban airspace and the deployment of flight tracking systems. A framework integrating multiple probabilistic methods is established. We formulate the event tree of pair-wise aircraft encounters with conflict detection provided by the tracking system. Then Monte Carlo simulation is performed by using an agent-based tool that we develop, to quantify the probability of event occurrences. Finally, Bayesian Networks models are built to infer the dependencies of conflict detection effectiveness on the airspace design and tracking system performances. The outcomes of this study demonstrate improvement in conflict detection that better tracking system performances can provide, and the impact of airspace design under different tracking configurations. The results can be used in the UAM traffic network planning, and systems standardization for UAM flight tracking, towards safe urban air traffic.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:244:y:2024:i:c:s0951832023008220
    DOI: 10.1016/j.ress.2023.109908
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023008220
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109908?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Mutlu, Arife Aycan, 2021. "The evaluation of Istanbul airspace design from the perspective of complexity and safety," Journal of Air Transport Management, Elsevier, vol. 97(C).
    3. 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.
    4. Hu, Xiaonong & Fang, Genshen & Yang, Jiayu & Zhao, Lin & Ge, Yaojun, 2023. "Simplified models for uncertainty quantification of extreme events using Monte Carlo technique," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    5. Blom, Henk A.P. & Jiang, Chenpeng & Grimme, Wouter B.A. & Mitici, Mihaela & Cheung, Yuk S., 2021. "Third party risk modelling of Unmanned Aircraft System operations, with application to parcel delivery service," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Pang, Bizhao & Hu, Xinting & Dai, Wei & Low, Kin Huat, 2022. "UAV path optimization with an integrated cost assessment model considering third-party risks in metropolitan environments," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Wang, Yuhao & Pang, Yutian & Chen, Oliver & Iyer, Hari N. & Dutta, Parikshit & Menon, P.K. & Liu, Yongming, 2021. "Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    8. Denney, Ewen & Pai, Ganesh & Whiteside, Iain, 2019. "The role of safety architectures in aviation safety cases," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Zhang, Yimin & Shortle, John & Sherry, Lance, 2015. "Methodology for collision risk assessment of an airspace flow corridor concept," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 444-455.
    10. Zou, Yiyuan & Zhang, Honghai & Zhong, Gang & Liu, Hao & Feng, Dikun, 2021. "Collision probability estimation for small unmanned aircraft systems," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhong, Gang & Du, Sen & Zhang, Honghai & Zhou, Jiangying & Liu, Hao, 2024. "Demarcation method of safety separations for sUAV based on collision risk estimation," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Zhou, Di & Zhuang, Xiao & Zuo, Hongfu & Cai, Jing & Zhao, Xufeng & Xiang, Jiawei, 2022. "A model fusion strategy for identifying aircraft risk using CNN and Att-BiLSTM," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Pang, Bizhao & Hu, Xinting & Dai, Wei & Low, Kin Huat, 2022. "UAV path optimization with an integrated cost assessment model considering third-party risks in metropolitan environments," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    4. Wu, Pengcheng & Chen, Jun, 2024. "Data-driven zonotopic approximation for n-dimensional probabilistic geofencing," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Ziegler Haselein, Bruno & da Silva, Jonny Carlos & Hooey, Becky L., 2024. "Multiple machine learning modeling on near mid-air collisions: An approach towards probabilistic reasoning," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    6. Ayoub, Ali & Stankovski, Andrej & Kröger, Wolfgang & Sornette, Didier, 2021. "Precursors and startling lessons: Statistical analysis of 1250 events with safety significance from the civil nuclear sector," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    7. Dui, Hongyan & Lu, Yaohui & Chen, Liwei, 2024. "Importance-based system cost management and failure risk analysis for different phases in life cycle," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    8. 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).
    9. Yazdi, Mohammad & Khan, Faisal & Abbassi, Rouzbeh & Quddus, Noor & Castaneda-Lopez, Homero, 2022. "A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    10. Chelouati, Mohammed & Boussif, Abderraouf & Beugin, Julie & El Koursi, El-Miloudi, 2023. "Graphical safety assurance case using Goal Structuring Notation (GSN) — challenges, opportunities and a framework for autonomous trains," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    11. Honghai Zhang & Yuhan Fei & Jingyu Li & Bowen Li & Hao Liu, 2022. "Method of Vertiport Capacity Assessment Based on Queuing Theory of Unmanned Aerial Vehicles," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    12. Zhou, Taotao & Zhang, Xiaoge & Droguett, Enrique Lopez & Mosleh, Ali, 2023. "A generic physics-informed neural network-based framework for reliability assessment of multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    13. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    14. Tian-yuan, Ye & Lin-lin, Liu & He-wei, Pang & Yuan-zi, Zhou, 2023. "Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    15. Gangolu, Jaswanth & Kumar, Ajay & Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Probabilistic demand models and performance-based fragility estimates for concrete protective structures subjected to missile impact," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    16. Liang, Xinrui & Fan, Shiqi & Lucy, John & Yang, Zaili, 2022. "Risk analysis of cargo theft from freight supply chains using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    17. 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.
    18. Ma, Hoi-Lam & Sun, Yige & Chung, Sai-Ho & Chan, Hing Kai, 2022. "Tackling uncertainties in aircraft maintenance routing: A review of emerging technologies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    19. Huanhuan Wang & Yong Zhang & Runqiu Li & Yan Cui & Andan He & Weiqing Jiang, 2023. "Analyzing the Risk Factors of Hazardous Chemical Road Transportation Accidents Based on Grounded Theory and a Bayesian Network," Sustainability, MDPI, vol. 15(24), pages 1-21, December.
    20. Liu, Tao & Bai, Guanghan & Tao, Junyong & Zhang, Yun-An & Fang, Yining, 2024. "A Multistate Network Approach for Resilience Analysis of UAV Swarm considering Information Exchange Capacity," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:244:y:2024:i:c:s0951832023008220. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.