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Data-driven micromobility network planning for demand and safety

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  • Pietro Folco
  • Laetitia Gauvin
  • Michele Tizzoni
  • Michael Szell

Abstract

Developing safe infrastructure for micromobility like bicycles or e-scooters is an efficient pathway towards climate-friendly, sustainable, and livable cities. However, urban micromobility infrastructure is typically planned ad-hoc and at best informed by survey data. Here, we study how data of micromobility trips and crashes can shape and automatize such network planning processes. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this tradeoff for the city of Turin. We find that a full focus on demand or safety generates different network extensions in the short term, with an optimal tradeoff in-between. In the long term, our framework improves overall network quality independent of short-term focus. Thus, we show how a data-driven process can provide urban planners with automated assistance for variable short-term scenario planning while maintaining the long-term goal of a sustainable, city-spanning micromobility network.

Suggested Citation

  • Pietro Folco & Laetitia Gauvin & Michele Tizzoni & Michael Szell, 2023. "Data-driven micromobility network planning for demand and safety," Environment and Planning B, , vol. 50(8), pages 2087-2102, October.
    • Handle: RePEc:sae:envirb:v:50:y:2023:i:8:p:2087-2102
    DOI: 10.1177/23998083221135611
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    References listed on IDEAS

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