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Authors: Gergely Kocsis and Imre Varga

Affiliation: Department of IT Systems and Networks, University of Debrecen, Kassai str. 26, Debrecen, Hungary

Keyword(s): GTFS, Public Transport, Networks.

Abstract: In several smart-city applications the networks of the mass-transportation systems can be bases of investigations. In this paper we show how one can extract a network of connected stops from the General Transit Feed Specification (GTFS) feed of a given service provider. We have also implemented this process as a tool (gtfs2net) that is available for use at the GitHub page of the project. On of our most important finding is that since providers do not follow the specification in a coherent way regarding the use of parent stations the problem of close stops has to be manually handled. In order to show how our tool works in practice we have provided some extracted networks with their properties.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kocsis, G. and Varga, I. (2022). Extracting Mass Transportation Networks from General Transit Feed Specification Datasets. In Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS, ISBN 978-989-758-565-4; ISSN 2184-5034, pages 85-91. DOI: 10.5220/0011080700003197

@conference{complexis22,
author={Gergely Kocsis. and Imre Varga.},
title={Extracting Mass Transportation Networks from General Transit Feed Specification Datasets},
booktitle={Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS,},
year={2022},
pages={85-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011080700003197},
isbn={978-989-758-565-4},
issn={2184-5034},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS,
TI - Extracting Mass Transportation Networks from General Transit Feed Specification Datasets
SN - 978-989-758-565-4
IS - 2184-5034
AU - Kocsis, G.
AU - Varga, I.
PY - 2022
SP - 85
EP - 91
DO - 10.5220/0011080700003197