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Risk-aware urban air mobility network design with overflow redundancy

Author

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  • Wei, Qinshuang
  • Gao, Zhenyu
  • Clarke, John-Paul
  • Topcu, Ufuk

Abstract

In urban air mobility (UAM), as envisioned by aviation professionals, novel flight vehicles will transport passengers and cargo at low altitudes within urban and suburban areas. To operate in urban environments, precise air traffic management, in particular the management of traffic overflows due to physical and operational disruptions will be critical to ensuring system safety and efficiency. To this end, we propose UAM network design with reserve capacity, i.e., a design where alternative landing options and flight corridors are explicitly considered as a means of improving contingency management. Similar redundancy considerations are incorporated in the design of many critical infrastructures, yet remain unexploited in the air transportation literature. In our methodology, we first model how disruptions to a given UAM network might impact on the nominal traffic flow and how this flow might be re-accommodated on an extended network with reserve capacity. Then, through an optimization problem, we select the locations and capacities for the backup vertiports with the maximal expected throughput of the extended network over all possible disruption scenarios, while the throughput is the maximal amount of flights that the network can accommodate per unit of time. We show that we can obtain the solution for the corresponding bi-level and bi-linear optimization problem by solving a mixed-integer linear program. We demonstrate our methodology in the case study using networks from Milwaukee, Atlanta, and Dallas–Fort Worth metropolitan areas and show how the throughput and flexibility of the UAM networks with reserve capacity can outcompete those without.

Suggested Citation

  • Wei, Qinshuang & Gao, Zhenyu & Clarke, John-Paul & Topcu, Ufuk, 2024. "Risk-aware urban air mobility network design with overflow redundancy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
  • Handle: RePEc:eee:transb:v:185:y:2024:i:c:s0191261524000912
    DOI: 10.1016/j.trb.2024.102967
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    References listed on IDEAS

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    1. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    2. Rajendran, Suchithra & Zack, Joshua, 2019. "Insights on strategic air taxi network infrastructure locations using an iterative constrained clustering approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 470-505.
    3. T. L. Magnanti & R. T. Wong, 1984. "Network Design and Transportation Planning: Models and Algorithms," Transportation Science, INFORMS, vol. 18(1), pages 1-55, February.
    4. Xu, Xiangdong & Chen, Anthony & Jansuwan, Sarawut & Yang, Chao & Ryu, Seungkyu, 2018. "Transportation network redundancy: Complementary measures and computational methods," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 68-85.
    5. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    6. Morlok, Edward K. & Chang, David J., 2004. "Measuring capacity flexibility of a transportation system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(6), pages 405-420, July.
    7. Liu, Zhiyuan & Wang, Zewen & Cheng, Qixiu & Yin, Ruyang & Wang, Meng, 2021. "Estimation of urban network capacity with second-best constraints for multimodal transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 276-294.
    8. Cohen, Adam P & Shaheen, Susan A PhD & Farrar, Emily M, 2021. "Urban Air Mobility: History, Ecosystem, Market Potential, and Challenges," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8nh0s83q, Institute of Transportation Studies, UC Berkeley.
    9. Bernat Joseph-Duran & Michael Jung & Carlos Ocampo-Martinez & Sebastian Sager & Gabriela Cembrano, 2014. "Minimization of Sewage Network Overflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 41-63, January.
    10. Boris S. Kerner, 2016. "The maximization of the network throughput ensuring free flow conditions in traffic and transportation networks: Breakdown minimization (BM) principle versus Wardrop’s equilibria," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(9), pages 1-17, September.
    11. Anthony Chen & Zhong Zhou & Piya Chootinan & Seungkyu Ryu & Chao Yang & S. Wong, 2011. "Transport Network Design Problem under Uncertainty: A Review and New Developments," Transport Reviews, Taylor & Francis Journals, vol. 31(6), pages 743-768.
    12. Suhyung Yoo & Hwasoo Yeo, 2016. "Evaluation of the resilience of air transportation network with adaptive capacity," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(sup1), pages 38-49, July.
    13. Chen, Anthony & Kasikitwiwat, Panatda, 2011. "Modeling capacity flexibility of transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 105-117, February.
    14. Yang, Hai & Bell, Michael G. H., 1998. "A capacity paradox in network design and how to avoid it," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 539-545, September.
    15. Dui, Hongyan & Chen, Shuanshuan & Zhou, Yanjie & Wu, Shaomin, 2022. "Maintenance analysis of transportation networks by the traffic transfer principle considering node idle capacity," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    16. Jansuwan, Sarawut & Chen, Anthony & Xu, Xiangdong, 2021. "Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 154-171.
    17. Litvak, Nelly & van Rijsbergen, Marleen & Boucherie, Richard J. & van Houdenhoven, Mark, 2008. "Managing the overflow of intensive care patients," European Journal of Operational Research, Elsevier, vol. 185(3), pages 998-1010, March.
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