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2080. How transport mode choices are influenced and what they mean for sustainable mobility: a data-driven study of the Asprela University Campus

Invited abstract in session TB-28: Advancements of OR-analytics in statistics, machine learning and data science 5, stream Advancements of OR-analytics in statistics, machine learning and data science.

Tuesday, 10:30-12:00
Room: 065 (building: 208)

Authors (first author is the speaker)

1. Sayeh Fooladi Mahani
INESC TEC, Faculty of Engineering, University of Porto
2. Beatriz Brito Oliveira
INESC TEC, Faculty of Engineering, University of Porto
3. Lia Patrício
Industrial Engineering and Management, INESC TEC and Faculty of Engineering, University of Porto
4. Vera Miguéis
INESC TEC, Faculty of Engineering, University of Porto
5. Maria Antónia Carravilla
INESC TEC, Faculty of Engineering, University of Porto
6. José Fernando Oliveira
INESC TEC, Faculty of Engineering, University of Porto

Abstract

This study aims to investigate sustainable urban transportation in the Asprela Campus at Porto. This area was chosen because three universities and a hospital are located there, and also attracts a variety of travelers such as students, workers, and visitors. This allows the study to explore the different preferences and perceptions that shape urban transportation. The study analyzes the choices of urban transportation, such as public transit, micro-mobility, ride-hailing, and car-sharing, made by individuals aged 18 years or older who commute to the area for various purposes, such as work, study, hospital visits, and others. To gather the data, the survey was developed in three parts, the initial part asks how the importance of the factors affecting transportation mode choices, then asks about the specific modes used to access the area, and finally asks socio-demographic information. The survey’s novelty is asking about factors affecting urban travel choices in the first part and examining actual behaviors in the second part, it gives a comprehensive view of urban transportation choices, closing the gap between preferences and real-world actions. The study’s results can help mobility companies and policymakers improve multi-modal transportation and sustainable mobility. It also finds key factors for choosing urban transportation modes, which can assist in developing enhanced demand models for urban mobility design and strategic decisions.

Keywords

Status: accepted

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