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May 17, 2026Case Studies on Transport PolicyOpen Access

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

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Authors

LCLucas Orbolato CarvalhoIGIgor Galhano GomesJRJaqueline Fonseca Rodrigues

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Overview

Randomized trial proposes a framework for optimizing urban air mobility networks in São Paulo, suggesting strategies for demand and infrastructure integration.

Key Points

  • The aim is to develop a data-driven framework for planning Urban Air Mobility (UAM) networks, focusing on socioeconomic factors and operational constraints.
  • Proposed an income-based spatial demand analysis model for UAM vertiport location.
  • Used clustering algorithms to identify high-demand vertiport sites based on income data.
  • Applied Dijkstra’s algorithm to optimize UAM routes connecting vertiports with airports.
  • Identified three high-income vertiport locations targeting the top 7.6% income distribution.
  • Estimated initial daily demand of approximately 186 UAM operations based on a weighted origin–destination matrix.
  • Demonstrated scalability of the network by expanding from 6 to 9 nodes and operations from 186 to 349.

Cite This Study

Carvalho et al. (2026) studied this question.

synapsesocial.com/papers/6a095b5d7880e6d24efe114chttps://doi.org/10.1016/j.cstp.2026.101848
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