Towards spatiotemporal integration of bus transit with data-driven approaches
<|reference_start|>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 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.<|reference_end|>
@article{borges2024towards,
    title={Towards spatiotemporal integration of bus transit with data-driven
  approaches},
    author={J'ulio Borges, Altieris M. Peixoto, Thiago H. Silva, Anelise
  Munaretto, Ricardo Luders},
    journal={arXiv preprint arXiv:2402.17866},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.17866},
    primaryClass={cs.SI cs.CE}
}