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Fast mission reliability prediction for Unmanned Aerial Vehicles

Author

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  • Andrews, J.D.
  • Poole, J.
  • Chen, W.H.

Abstract

There is currently a significant interest in the use of autonomous vehicles in many industrial sectors. One such example is the ever increasing use of Unmanned Aerial Vehicles (UAVs), particularly in military operations. This enables dangerous missions to be accomplished without risk to a pilot. UAVs also have potential civil applications which would require their certification and the demonstration that they are able to respond safety to any potential circumstances. The aircraft would therefore need to be capable of responding safely to the occurrence of component failures, the emergence of threats such as other aircraft in the neighboring airspace, and changing weather conditions. The likelihood that an aircraft will successfully complete any mission can be predicted using phased mission analysis techniques. The predicted mission unreliability can be updated in response to changing circumstances. In the event that the likelihood of mission failure becomes too high then changes have to be made to the mission plan. If these calculations could be carried out fast enough then the quantification procedure could be used to establish an acceptable response to any new conditions. With a view to using the methodology in the context described above, this paper investigates ways in which phased mission analysis can be improved to reduce the calculation time. The methodology improves the processing capability for a UAV phased mission analysis by taking into account the specific characteristics of the fault tree structures which provide the causes of phase failure for a UAV mission. It also carries out as much of the quantification as possible in advance of the mission plan being formulated.

Suggested Citation

  • Andrews, J.D. & Poole, J. & Chen, W.H., 2013. "Fast mission reliability prediction for Unmanned Aerial Vehicles," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 3-9.
  • Handle: RePEc:eee:reensy:v:120:y:2013:i:c:p:3-9
    DOI: 10.1016/j.ress.2013.03.002
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    References listed on IDEAS

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    1. D R Prescott & R Remenyte-Prescott & S Reed & J D Andrews & C G Downes, 2009. "A reliability analysis method using binary decision diagrams in phased mission planning," Journal of Risk and Reliability, , vol. 223(2), pages 133-143, June.
    2. Remenyte-Prescott, R. & Andrews, J.D. & Chung, P.W.H., 2010. "An efficient phased mission reliability analysis for autonomous vehicles," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 226-235.
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    Citations

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    Cited by:

    1. Hua Yan & Pu Long Cui & Yi Sheng Wang & Fei Wan & De Li & Bi Xing Li, 2018. "A Hierarchical Reduced Markov Model for Reliability Evaluation of Phased-Mission Systems," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 11(4), pages 8637-8640, November.
    2. Jung, Woo Sik, 2015. "A method to improve cutset probability calculation in probabilistic safety assessment of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 134-142.
    3. Feng, Qiang & Liu, Meng & Dui, Hongyan & Ren, Yi & Sun, Bo & Yang, Dezhen & Wang, Zili, 2022. "Importance measure-based phased mission reliability and UAV number optimization for swarm," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Dui, Hongyan & Zhang, Chi & Bai, Guanghan & Chen, Liwei, 2021. "Mission reliability modeling of UAV swarm and its structure optimization based on importance measure," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Zhao, Xian & Lv, Zuheng & Qiu, Qingan & Wu, Yaguang, 2023. "Designing two-level rescue depot location and dynamic rescue policies for unmanned vehicles," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Hu, Bin & Seiler, Peter, 2015. "Pivotal decomposition for reliability analysis of fault tolerant control systems on unmanned aerial vehicles," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 130-141.

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