Data underlying the publication: Service Design and Frequency Setting for the European High-Speed Rail Network
doi:10.4121/ea9f1238-0cc8-47ba-b8c6-3e0846fb8d19.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/ea9f1238-0cc8-47ba-b8c6-3e0846fb8d19
doi: 10.4121/ea9f1238-0cc8-47ba-b8c6-3e0846fb8d19
Datacite citation style:
Grolle, Jorik; Donners, Barth; Jan Anne Annema; Duinkerken, Mark; Cats, Oded (2023): Data underlying the publication: Service Design and Frequency Setting for the European High-Speed Rail Network. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/ea9f1238-0cc8-47ba-b8c6-3e0846fb8d19.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
CC0
We present a customised version of the Transit Network Design and Frequency Setting Problem (TNDFSP) for the long-distance transport context and HSR in particular. This allows to asses the potential of design and policy choices for HSR network design. We apply an adapted version of a heuristic solution approach to analyse the users’, operators’ and societal performance of a European HSR-network by conducting an extensive series of experiments to test the network’s performance under various policy priorities and HSR design variables. This dataset contains the two python scripts used: the first to estimate long-distance travel demand and secondly our heuristic solution approach to solve the TNDFSP. Also, input data is included , which allows to run the scripts for new experiments
history
- 2023-08-17 first online, published, posted
publisher
4TU.ResearchData
format
zipped (python2-files, excel-files, PDF-files)
references
funding
- None
organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and PlanningTU Delft, Faculty of Technology, Policy and Management, Department of Transport and Logistics
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Department of Transport Engineering and Logistics
Royal HaskoningDHV
DATA
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download all files (zip)
27,450,976 bytes unzipped
