Applying Data Analytics to Analyze Activity Sequences for an Assessment of Fragmentation in Daily Travel Patterns: A Case Study of the Metropolitan Region of Barcelona

Lídia Montero (), Lucía Mejía-Dorantes and Jaume Barceló
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Lídia Montero: Department of Statistics and Operations Reserach, Universitat Politècnica de Catalunya (UPC), C5 2nd Floor, Campus Nord, C\Jordi Girona, 1-3, 08034 Barcelona, Spain
Lucía Mejía-Dorantes: Independent Researcher, 76185 Karlsruhe, Germany
Jaume Barceló: Department of Statistics and Operations Reserach, Universitat Politècnica de Catalunya (UPC), C5 2nd Floor, Campus Nord, C\Jordi Girona, 1-3, 08034 Barcelona, Spain

Sustainability, 2023, vol. 15, issue 19, 1-22

Abstract: Sequence analysis is a robust methodological approach that has gained popularity in various fields, including transportation research. It provides a comprehensive way to understand the dynamics and patterns of individual behaviors over time. In the context of the Metropolitan Region of Barcelona, applying sequence analysis to mobility surveys offers valuable insights into the sequencing of travel activities and modes, shedding light on the complex interrelationship between individuals and their travel choices and the built environment. Sequence analysis allows us to examine travel behaviors as dynamic processes and reveal the underlying structure and evolution of travel patterns over a day. Here, we describe a data analytics approach that enables the identification of common travel patterns and the exploration of variations across demographic groups or geographical regions. We propose a method for discovering similarities in travel behavior segments from diaries included in travel surveys in order to refine transport policies for selected segments. Unfortunately, the data collected by the authorities in the analyzed travel surveys do not include family structure, which seems critical in explaining the segmentation of travel sequences.

Keywords: travel behavior; sequence analysis; classification analysis; spatial analysis; gender issues (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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