Public Transport Stops State Detection and Propagation - Warsaw Use Case

Marcin Luckner, Paweł Kobojek, Paweł Zawistowski

2017

Abstract

Publication of information on public transport in a form acceptable to third–party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones.

References

  1. Álvarez, A., Casado, S., González Velarde, J. L., and Pacheco, J. (2010). A computational tool for optimizing the urban public transport: A real application. Journal of Computer and Systems Sciences International, 49(2):244-252.
  2. Chunithipaisan, S. and Supavetch, S. (2009). The development of web processing service using the power of spatial database. In Emerging Trends in Engineering and Technology (ICETET), 2009 2nd International Conference on, pages 832 -837.
  3. García, C. R., Pérez, R., Lorenz, Á., Alayón, F., and Padrón, G. (2009). Supporting information services for travellers of public transport by road. In Computer Aided Systems Theory - EUROCAST 2009: 12th International Conference, pages 406-412, Berlin, Heidelberg. Springer Berlin Heidelberg.
  4. Grabowski, S., Grzenda, M., and Legierski, J. (2015). The adoption of open data and open api telecommunication functions by software developers. In Business Information Systems: 18th International Conference, Proceedings, pages 337-347, PoznaÁ, Poland,. Springer International Publishing.
  5. Grzenda, M., Kaczmarski, K., Kobos, M., and Luckner, M. (2011). Geospatial presentation of purchase transactions data. In FedCSIS, pages 291-296.
  6. Lakomaa, E. and Kallberg, J. (2013). Open data as a foundation for innovation: The enabling effect of free public sector information for entrepreneurs. IEEE Access, 1:558-563.
  7. Lindman, J., Kinnari, T., and Rossi, M. (2014). Industrial open data: Case studies of early open data entrepreneurs. In 2014 47th Hawaii International Conference on System Sciences, pages 739-748.
  8. Nesheli, M. M., Ceder, A. A., and Estines, S. (2016). Public transport user's perception and decision assessment using tactic-based guidelines. Transport Policy, 49:125 - 136.
  9. Open Geospatial Consortium (2007). OpenGIS Geography Markup Language (GML) Encoding Standard(Version 3.2.1) [EB/OL].
  10. Open Geospatial Consortium (2009a). OpenGIS Web Feature Service (WFS) Implementation Specification Version 1.1.0.
  11. Open Geospatial Consortium (2009b). OpenGIS Web Map Service (WMS) Implementation Specification Version 1.3.0.
  12. Rathod, R. and Khot, S. T. (2016). Smart assistance for public transport system. In 2016 International Conference on Inventive Computation Technologies (ICICT), volume 3, pages 1-5.
  13. Ribeiro, J., de Farias, O., and Roque, L. (2004). A syntactic and lexicon analyzer for the geography markup language (gml). In Geoscience and Remote Sensing Symposium, 2004. IGARSS 7804. Proceedings. 2004 IEEE International, volume 5, pages 2896 - 2899 vol.5.
  14. Rodrigues, F., Borysov, S., Ribeiro, B., and Pereira, F. (2016). A bayesian additive model for understanding public transport usage in special events. IEEE Transactions on Pattern Analysis and Machine Intelligence, PP(99):1-1.
  15. Tyrinopoulos, Y. (2004). A complete conceptual model for the integrated management of the transportation work. Journal of Public Transportation, 7(4):101-121.
  16. Ying-Jun, D., Chong-Chong, Y., and Jie, L. (2009). A study of gis development based on kml and google earth. In INC, IMS and IDC, 2009. NCM 7809., pages 1581 -1585.
  17. Zheng, P., Wang, W., and Ge, H. (2016). The influence of bus stop on traffic flow with velocity-differenceseparation model. International Journal of Modern Physics C, 27(11):1650135.
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Paper Citation


in Harvard Style

Luckner M., Kobojek P. and Zawistowski P. (2017). Public Transport Stops State Detection and Propagation - Warsaw Use Case . In Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-241-7, pages 235-241. DOI: 10.5220/0006305102350241


in Bibtex Style

@conference{smartgreens17,
author={Marcin Luckner and Paweł Kobojek and Paweł Zawistowski},
title={Public Transport Stops State Detection and Propagation - Warsaw Use Case},
booktitle={Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2017},
pages={235-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006305102350241},
isbn={978-989-758-241-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Public Transport Stops State Detection and Propagation - Warsaw Use Case
SN - 978-989-758-241-7
AU - Luckner M.
AU - Kobojek P.
AU - Zawistowski P.
PY - 2017
SP - 235
EP - 241
DO - 10.5220/0006305102350241