AI-Powered Urban Digital Twins for Resilient, Sustainable, and Safe Cities: Democratizing Citizen Deliberation on Urban Air Mobility Futures

Yiping Yan , Bangyang Wei , Yang Liu , Xiaobo Qu

Engineering ›› : 202605007

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Engineering ›› :202605007 DOI: 10.1016/j.eng.2026.05.007
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AI-Powered Urban Digital Twins for Resilient, Sustainable, and Safe Cities: Democratizing Citizen Deliberation on Urban Air Mobility Futures
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Yiping Yan, Bangyang Wei, Yang Liu, Xiaobo Qu. AI-Powered Urban Digital Twins for Resilient, Sustainable, and Safe Cities: Democratizing Citizen Deliberation on Urban Air Mobility Futures. Engineering 202605007 DOI:10.1016/j.eng.2026.05.007

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References

[1]

Sengupta R, Bulusu V, Mballo CE, Onat EB, Cao S . Urban air mobility research challenges and opportunities. Annu Rev Control Robot Auton Syst 2025; 8(1):407-31.

[2]

Garrow LA, German BJ, Leonard CE . Urban air mobility: a comprehensive review and comparative analysis with autonomous and electric ground transportation for informing future research. Transp Res Part C Emerg Technol 2021; 132:103377.

[3]

Acuto M, Parnell S, Seto KC . Building a global urban science. Nat Sustain 2018;1(1):2-4.

[4]

Federal Aviation Administration . Urban Air Mobility (UAM) concept of operations, v2.0. Report. Washington: U.S. Department of Transportation; 2023.

[5]

European Commission . Commission implementing regulation (EU) 2021/664 on a regulatory framework for the U—space. Off J Eur Union L 2021; 139:161-83.

[6]

Cohen AP, Shaheen SA, Farrar EM . Urban air mobility: history, ecosystem, market potential, and challenges. IEEE Trans Intell Transp Syst 2021; 22(9):6074—87.

[7]

Bustos Moreno Y . The implementation of U—space: open challenges from the legal—private perspective. In: Governance and control of data and digital economy in the European single market: legal framework for new digital assets, identities and data spaces. Cham: Springer Nature Switzerland; 2025. p. 489-515.

[8]

Wang Z, Lv D, Jia S, Wang K, Qu X . Urban air mobility network design and operations strategy in an urban agglomeration. Transp Res Part E Logist Trans Rev 2025; 203:104316.

[9]

Weil C, Bibri SE, Longchamp R, Golay F, Alahi A . Urban digital twin challenges: a systematic review and perspectives for sustainable smart cities. Sustain Cities Soc 2023; 99:104862.

[10]

Grieves M, Vickers J . Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary perspectives on complex systems: new findings and approaches. Cham: Springer International Publishing; 2016. p. 85-113.

[11]

Barricelli BR, Casiraghi E, Fogli D . A survey on digital twin: definitions, characteristics, applications, and design implications. IEEE Access 2019; 7:167653—71.

[12]

Thelen A, Zhang X, Fink O, Lu Y, Ghosh S, Youn BD, et al. A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives. Struct Multidiscipl Optim 2023; 66(1):1.

[13]

Pearl J, Mackenzie D . The book of why: the new science of cause and effect. London: Penguin UK; 2018.

[14]

Luo J, Liu P, Kong X, Shen J, Wu Q, Xu D . Urban digital twins for citizen—centric planning: a systematic review of built environment perception and public participation. Int J Appl Earth Obs Geoinf 2025; 143:104746.

[15]

Yang Y, Zhan J, Liu Y, Wang Q . Cross—city transfer learning: applications and challenges for smart cities and sustainable transportation. Commun Transp Res 2025; 5:100206.

[16]

Yeon H, Eom T, Jang K, Yeo J . DTUMOS, digital twin for large—scale urban mobility operating system. Sci Rep 2023; 13(1):5154.

[17]

Dassault Systèmes. Virtual Singapore [Internet]. France:Dassault Systèmes ; undated [cited 2026 May 15]. Available from:https://www.3ds.com/insights/customer—stories/virtual—singapore.

[18]

City of Helsinki . The Kalasatama digital twins project: the final report of the KIRA—digi pilot project. Report. Helsinki: KIRA—digi; 2019.

[19]

Torija AJ, Li Z, Self RH . Effects of a hovering unmanned aerial vehicle on urban soundscapes perception. Transp Res Part D Transp Environ 2020; 78:102195.

[20]

Rizzi SA . Characterization of urban air mobility vehicle operational noise and community noise impact. In: Proceedings of the AIAA Tech Talk Series; 2022 Mar 22; Hampton, VA, USA. Hampton: NASA Langley Research Center; 2022. p. 20220016894.

[21]

Hu ZQ, Xu MX, Cheng QX . Multimodal large—language model empowering next—generation autonomous driving systems. J Intell Connect Veh 2025; 8(2):9210059—1.

[22]

Adade D, de Vries WT . A systematic review of digital twins’ potential for citizen participation and influence in land use agenda—setting. Discov Sustain 2025; 6(1):354.

[23]

Yang Y, Zhan J, Xu M, Liu Y, Qu X . Toward climate—neutral urban mobility: understanding shared e—scooter carbon emission patterns through multi—city evidence in Europe. Transp Res Part A Policy Pract 2026; 203:104736.

[24]

Guo T, Wu H, Zame SI, Antoniou C . Data—driven vertiport siting: a comparative analysis of clustering methods for Urban Air Mobility. J Urban Mobil 2025; 7:100117.

[25]

Lv D, Wang K, Chen S, Qu X . Flying cars and urban air mobility: redefining cities in three dimensions. Commun Transp Res 2025; 5(4):100213.

[26]

Dwork C, McSherry F, Nissim K, Smith A . Calibrating noise to sensitivity in private data analysis. In: Theory of cryptography conference. Berlin: Springer; 2006. p. 265-84.

[27]

Wheaton WD, Cajka JC, Chasteen BM, Wagener DK, Cooley PC, Ganapathi L, et al. Synthesized population databases: a US geospatial database for agent—based models. Report. Durham: RTI Press; 2009.

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