Data-driven framework for urban air mobility planning: Integrating socioeconomic and operational factors for optimal network design in São Paulo, Brazil

Lucas Orbolato Carvalho; Igor Galhano Gomes; Jaqueline Fonseca Rodrigues; Mayara Condé Rocha Murça; Marcelo Xavier Guterres; Daniel Alberto Pamplona

doi:10.1016/j.cstp.2026.101848

Publication

Case Studies on Transport Policy, Volume 25, Article 101848 (2026). DOI: 10.1016/j.cstp.2026.101848.

Publisher / DOI ResearchGate Author homepage

Study summary

This case study develops a data-driven framework for initial Urban Air Mobility network planning in the São Paulo Metropolitan Region. It integrates socioeconomic demand information, existing helipad infrastructure, vertiport siting, origin-destination demand estimation, route design and operational constraints. Partitioning Around Medoids clustering is used to identify candidate vertiport locations, while the existing helicopter route structure is reused to construct conflict- and distance-minimized connections compatible with an incremental deployment strategy. The resulting network supports an illustrative daily demand of 186 UAM operations and emphasizes infrastructure reuse as a way to reduce initial implementation barriers. The framework is intended as a transferable planning methodology rather than a forecast of realized UAM demand, and it highlights the interaction between market viability, aeronautical infrastructure and airspace constraints in early network design.

Keywords: urban air mobility; vertiport location; route optimization; demand estimation; airspace design; clustering.

BibTeX

@article{Carvalho2026UAMPlanning, author = {Carvalho, Lucas Orbolato and Gomes, Igor Galhano and Rodrigues, Jaqueline Fonseca and Murça, Mayara Condé Rocha and Guterres, Marcelo Xavier and Pamplona, Daniel Alberto}, title = {Data-driven framework for urban air mobility planning: Integrating socioeconomic and operational factors for optimal network design in São Paulo, Brazil}, journal = {Case Studies on Transport Policy}, volume = {25}, pages = {101848}, year = {2026}, doi = {10.1016/j.cstp.2026.101848} }

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