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Title	Towards Spatiotemporal Integration Of Bus Transit With Data-Driven Approaches
ID_Doc	58357
Authors	Borges J.C.; Peixoto A.M.; Silva T.H.; Munaretto A.; Lüders R.
Year	2024
Published	Journal of Internet Services and Applications, 15, 1
DOI	http://dx.doi.org/10.5753/JISA.2024.3812
Abstract	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 transit 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. © 2024, J. Internet Serv. Appl. All rights reserved.
Author Keywords	bus transit network; data-driven model; smart city; spatiotemporal integration; urban computing

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