Histograms of traffic data of Baltimore Light RailLink Data supplied by the
We acknowledge Swiftly’s GTFS-realtime API https://swiftly.zendesk.com/hc/en-us (accessed 11-31 January 2024) for supplying these real-time traffic data.
of passing times between selected stations use
hist --datafolder ... --direction
where: --datafolder (multiple) arguments of files input \outputs --direction trains direction possible "n" north, "s" south "" both.
Plots are saved in \pics.
Example plotter:
python3 hists.py --datafolder "11012024_700/" "12012024_700/" "15012024_700/" "16012024_700/" "11012024_1500/" "12012024_1500/" "15012024_1500/" "16012024_1500/" --direction "n"
For data quality check, compare with manually collected data in folder description/Dane KG.xls
For precise data/system description (in Polish) see folder description/expertises
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M. Koniorczyk, K. Krawiec, L. Botelho, N. Bešinović, and K. Domino, "Solving rescheduling problems in heterogeneous urban railway networks using hybrid quantum-classical approach", Journal of Rail Transport Planning & Management, vol. 34, issue 100521, 05/2025, https://doi.org/10.1016/j.jrtpm.2025.100521
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K. Domino, E. Doucet, R. Robertson, B. Gardas, and S. Deffner, "On the Baltimore Light RailLink into the quantum future", Scientific Reports, vol. 15, issue 29576, 08/2025, 10.1038/s41598-025-15545-0
The code was partially supported by Polish National Science Center under grant agreement number 2023/07/X/ST6/00396.