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The Use of UAVs in Humanitarian Relief: An Application of POMDP‐Based Methodology for Finding Victims

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  • Raissa Zurli Bittencourt Bravo
  • Adriana Leiras
  • Fernando Luiz Cyrino Oliveira

Abstract

Researchers have proposed the use of unmanned aerial vehicles (UAVs) in humanitarian relief to search for victims in disaster‐affected areas. Once UAVs must search through the entire affected area to find victims, the path‐planning operation becomes equivalent to an area coverage problem. In this study, we propose an innovative method for solving such problem based on a Partially Observable Markov Decision Process (POMDP), which considers the observations made from UAVs. The formulation of the UAV path planning is based on the idea of assigning higher priorities to the areas that are more likely to have victims. We applied the method to three illustrative cases, considering different types of disasters: a tornado in Brazil, a refugee camp in South Sudan, and a nuclear accident in Fukushima, Japan. The results demonstrated that the POMDP solution achieves full coverage of disaster‐affected areas within a reasonable time span. We evaluate the traveled distance and the operation duration (which were quite stable), as well as the time required to find groups of victims by a detailed multivariate sensitivity analysis. The comparisons with a Greedy Algorithm showed that the POMDP finds victims more quickly, which is the priority in humanitarian relief, whereas the performance of the Greedy focuses on minimizing the traveled distance. We also discuss the ethical, legal, and social acceptance issues that can influence the application of the proposed methodology in practice.

Suggested Citation

  • Raissa Zurli Bittencourt Bravo & Adriana Leiras & Fernando Luiz Cyrino Oliveira, 2019. "The Use of UAVs in Humanitarian Relief: An Application of POMDP‐Based Methodology for Finding Victims," Production and Operations Management, Production and Operations Management Society, vol. 28(2), pages 421-440, February.
    • Handle: RePEc:bla:popmgt:v:28:y:2019:i:2:p:421-440
    DOI: 10.1111/poms.12930
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    Citations

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    Cited by:

    1. Mao Hong & Zhengling Qi & Yanxun Xu, 2023. "A Policy Gradient Method for Confounded POMDPs," Papers 2305.17083, arXiv.org, revised Nov 2023.
    2. Raissa Zurli Bittencourt Bravo & Ana Paula Martins do Amaral Cunha & Adriana Leiras & Fernando Luiz Cyrino Oliveira, 2021. "A new approach for a drought composite index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 755-773, August.
    3. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    4. Zhaoxia Guo & Qinqin Guo & Yujie Cai & Ge Wang, 2021. "Unraveling Risk Networks of Cultivated Land Protection: An Exploratory Stakeholder-Oriented Case Study in Xiliuhe Town, Hubei Province, China," Land, MDPI, vol. 10(11), pages 1-26, November.
    5. Sandun Perera & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2020. "Retail Deliveries by Drones: How Will Logistics Networks Change?," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2019-2034, September.
    6. Zhu, Xiaoning & Yan, Rui & Peng, Rui & Zhang, Zhongxin, 2020. "Optimal routing, loading and aborting of UAVs executing both visiting tasks and transportation tasks," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Marlena Robakowska & Daniel Ślęzak & Przemysław Żuratyński & Anna Tyrańska-Fobke & Piotr Robakowski & Paweł Prędkiewicz & Katarzyna Zorena, 2022. "Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies," IJERPH, MDPI, vol. 19(17), pages 1-15, August.
    8. Wang, Yan & Wang, Junwei, 2019. "Integrated reconfiguration of both supply and demand for evacuation planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 82-94.
    9. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    10. Merkert, Rico & Bushell, James, 2020. "Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control," Journal of Air Transport Management, Elsevier, vol. 89(C).
    11. Yan, Rui & Zhu, Xiaoping & Zhu, Xiaoning & Peng, Rui, 2023. "Joint optimisation of task abortions and routes of truck-and-drone systems under random attacks," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Lorena Reyes-Rubiano & Jana Voegl & Klaus-Dieter Rest & Javier Faulin & Patrick Hirsch, 2021. "Exploration of a disrupted road network after a disaster with an online routing algorithm," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 289-326, March.

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