EURO 2024 Copenhagen
Abstract Submission

EURO-Online login

247. Characterizing last-mile freight transport using mobile phone data: The case of Santiago, Chile

Invited abstract in session MA-56: Last mile delivery modeling, stream Transportation.

Monday, 8:30-10:00
Room: S04 (building: 101)

Authors (first author is the speaker)

1. Raul Pezoa
Universidad Diego Portales

Abstract

Understanding the mobility of ground freight transport is critical in urban planning and for developing public policies. Literature shows that most of the previous studies on this topic rely on surveys and limited data, hindering the accuracy of the analysis. To cope with this drawback, in this paper, we present an innovative methodology for characterizing last-mile freight transport that uses a novel data source: mobile phone data, which offers the advantage of a broader coverage compared to data sources used in previous contributions. To the best of our knowledge, no prior articles have employed mobile phone data sources to study freight transport. To bridge this gap, we propose a methodology that calibrates supervised machine learning models to determine which cell phones correspond to truck drivers. To do so, we construct input variables that seek to track the daily movement patterns of mobile phones, including traveled distances, interactions with highway networks, and land use variables. We test our approach by conducting a case study in Santiago, Chile, for which we analyze mobility patterns and logistic indicators disaggregated by day, hour, and zoning. Our results show high activity in Santiago's outskirts, especially in the northwest and southwest areas, with many interactions due to logistic centers and industrial zones. Similarly, central and eastern Santiago also show high stop density, reflecting intense commercial activity.

Keywords

Status: accepted

Back to the list of papers