Towards spatiotemporal integration of bus transit with data-driven approaches
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916141319847936 |
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| 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 |