Towards spatiotemporal integration of bus transit with data-driven approaches

Fuente: arXiv
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Main Authors: Borges, Júlio, Peixoto, Altieris M., Silva, Thiago H., Munaretto, Anelise, Luders, Ricardo
Format: Preprint
Published: 2024
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_version_ 1866916141319847936
author Borges, Júlio
Peixoto, Altieris M.
Silva, Thiago H.
Munaretto, Anelise
Luders, Ricardo
author_facet Borges, Júlio
Peixoto, Altieris M.
Silva, Thiago H.
Munaretto, Anelise
Luders, Ricardo
contents This study aims to propose an approach for spatiotemporal integration of bus transit, which enables users to change bus lines by paying a single fare. This could increase bus transit efficiency and, consequently, help to make this mode of transportation more attractive. Usually, this strategy is allowed for a few hours in a non-restricted area; thus, certain walking distance areas behave like "virtual terminals." For that, two data-driven algorithms are proposed in this work. First, a new algorithm for detecting itineraries based on bus GPS data and the bus stop location. The proposed algorithm's results show that 90% of the database detected valid itineraries by excluding invalid markings and adding times at missing bus stops through temporal interpolation. Second, this study proposes a bus stop clustering algorithm to define suitable areas for these virtual terminals where it would be possible to make bus transfers outside the physical terminals. Using real-world origin-destination trips, the bus network, including clusters, can reduce traveled distances by up to 50%, making twice as many connections on average.
format Preprint
id arxiv_https___arxiv_org_abs_2402_17866
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Towards spatiotemporal integration of bus transit with data-driven approaches
Borges, Júlio
Peixoto, Altieris M.
Silva, Thiago H.
Munaretto, Anelise
Luders, Ricardo
Social and Information Networks
Computational Engineering, Finance, and Science
This study aims to propose an approach for spatiotemporal integration of bus transit, which enables users to change bus lines by paying a single fare. This could increase bus transit efficiency and, consequently, help to make this mode of transportation more attractive. Usually, this strategy is allowed for a few hours in a non-restricted area; thus, certain walking distance areas behave like "virtual terminals." For that, two data-driven algorithms are proposed in this work. First, a new algorithm for detecting itineraries based on bus GPS data and the bus stop location. The proposed algorithm's results show that 90% of the database detected valid itineraries by excluding invalid markings and adding times at missing bus stops through temporal interpolation. Second, this study proposes a bus stop clustering algorithm to define suitable areas for these virtual terminals where it would be possible to make bus transfers outside the physical terminals. Using real-world origin-destination trips, the bus network, including clusters, can reduce traveled distances by up to 50%, making twice as many connections on average.
title Towards spatiotemporal integration of bus transit with data-driven approaches
topic Social and Information Networks
Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2402.17866