Towards spatiotemporal integration of bus transit with data-driven approaches
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 all...
| Autores: | , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2024 |
| País: | Brasil |
| Recursos: | Sociedade Brasileira de Computação (SBC) |
| Repositório: | Journal of internet services and applications (Internet) |
| Idioma: | inglês |
| OAI Identifier: | oai:journals-sol.sbc.org.br:article/3812 |
| Acesso em linha: | https://journals-sol.sbc.org.br/index.php/jisa/article/view/3812 |
| Access Level: | Acceso aberto |
| Palavra-chave: | bus transit network spatiotemporal integration data-driven model urban computing smart city |
| Resumo: | 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%, at the expense of making twice as many connections on average. |
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