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Towards Formal, Graph-Based Spatial Data Processing: The Case of Lighting Segments for Pedestrian Crossings

  • Sebastian ErnstEmail author
  • Leszek Kotulski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11431)

Abstract

The paper proposes a graph formalism for flexible and efficient manipulation of geospatial data. Its main practical application is preparation of data for lighting optimisation projects in conformance with regulations. The formalism is based on the extended Semantic Environment Graph, already proposed in our previous work. A simple example of a one-way street with a pedestrian crossing is used to illustrate each step of the proposed procedure. The process involves executing a series of graph productions, which introduce the new shapes into the data. Implementation is not the main focus of the paper, but results of conducted studies are provided to present the practical implications of the proposed method, compared to the traditional approach used by lighting designers.

Keywords

Graph transformations Geospatial modelling Road lighting Energy efficiency 

References

  1. 1.
    PostGIS 2.4 Documentation. https://postgis.net/docs/manual-2.4/. Accessed 4 Oct 2018
  2. 2.
    NBN L 18–002: Recommendations for special cases of public lighting. Technical report, Bureau voor Normalisatie, January 1988Google Scholar
  3. 3.
    Technical Report 12: Lighting of Pedestrian Crossings. Technical report, Institution of Lighting Engineers (2007)Google Scholar
  4. 4.
    DIN 67523–2:2010–06: Beleuchtung von Fußgängerüberwegen (Zeichen 293 StVO) mit Zusatzbeleuchtung - Teil 2: Berechnung und Messung. Technical report, Deutsches Institut für Normung, June 2010Google Scholar
  5. 5.
    Linee guida per la progettazione degli attraversamenti pedonali. Technical report, Automobile Club d’Italia (2011)Google Scholar
  6. 6.
    CEN/TR 13201–1: Road lighting – Part 1: Guidelines on selection of lighting classes. Technical report, European Committee for Standarization, December 2014Google Scholar
  7. 7.
    EN 13201–2: Road lighting – Part 2: Performance requirements. Technical report, European Committee for Standarization, December 2014Google Scholar
  8. 8.
    EN 13201–3: Road lighting – Part 3: Calculation of performance. Technical report, European Committee for Standarization, December 2014Google Scholar
  9. 9.
    EN 13201–4: Road lighting – Part 4: methods of measuring lighting performance. Technical report, European Committee for Standarization, December 2014Google Scholar
  10. 10.
    Håndbok N100: Veg-og gateutforming. Technical report, Statens vegvesen (2014)Google Scholar
  11. 11.
    prEN 13201–5: Road lighting – Part 5: Energy performance indicators. Technical report, European Committee for Standarization, December 2014Google Scholar
  12. 12.
    Vägbelysningshandboken. Technical report, Trafikverket (2014)Google Scholar
  13. 13.
    Krav för vägars och gators utformning. Technical report Trafikverkets publikation 2015:086, Trafikverket, Sveriges Kommuner och Landsting (2015)Google Scholar
  14. 14.
    Osvětlení pozemních komunikací. In: Technické Kvalitativní Podmínky Staveb. Ministerstvo Dopravy (2015)Google Scholar
  15. 15.
    Beleuchtung von Fussgänger-Überwegen. In: SLG Richtlinie 202:2016. Schweizer Licht Gesellschaft (2016)Google Scholar
  16. 16.
    Date, C.J.: A Guide to the SQL Standard: A User’s Guide to the Standard Relational Language SQL. Addison-Wesley Longman Publishing Co., Inc., Boston (1987)Google Scholar
  17. 17.
    Ernst, S., Łabuz, M., Środa, K., Kotulski, L.: Graph-based spatial data processing and analysis for more efficient road lighting design. Sustainability 10(11), 3850 (2018).  https://doi.org/10.3390/su10113850CrossRefGoogle Scholar
  18. 18.
    Gómez-Lorente, D., Rabaza, O., Espín Estrella, A., Peña-García, A.: A new methodology for calculating roadway lighting design based on a multi-objective evolutionary algorithm. Expert Syst. Appl. 40(6), 2156–2164 (2013).  https://doi.org/10.1016/j.eswa.2012.10.026CrossRefGoogle Scholar
  19. 19.
    Hölker, F., Wolter, C., Perkin, E.K., Tockner, K.: Light pollution as a biodiversity threat. Trends Ecol. Evol. 25(12), 681–682 (2010).  https://doi.org/10.1016/j.tree.2010.09.007CrossRefGoogle Scholar
  20. 20.
    Jamroz, K., Tomczuk, P., Mackun, T., Chrzanowicz, M.: Wytyczne prawidłowego oświetlenia przejść dla pieszych. Technical report, Ministerstwo Infrastruktury (2018)Google Scholar
  21. 21.
    Ministerie van de Vlaamse Gemeenschap Ministerie van de Vlaamse Gemeenschap: Ontwerprichtlijnen voor Voetgangersvoorzieningen. In: Vademecum Voetgangersvoorzieningen (2003)Google Scholar
  22. 22.
    Rabaza, O., Peña-García, A., Pérez-Ocón, F., Gómez-Lorente, D.: A simple method for designing efficient public lighting, based on new parameter relationships. Expert Syst. Appl. 40(18), 7305–7315 (2013).  https://doi.org/10.1016/j.eswa.2013.07.037CrossRefGoogle Scholar
  23. 23.
    Sędziwy, A.: Sustainable street lighting design supported by hypergraph-based computational model. Sustainability 8(1), 13 (2015).  https://doi.org/10.3390/su8010013CrossRefGoogle Scholar
  24. 24.
    Wojnicki, I., Kotulski, L.: Empirical study of how traffic intensity detector parameters influence dynamic street lighting energy consumption: a case study in Krakow, Poland. Sustainability 10(4), 1221 (2018).  https://doi.org/10.3390/su10041221CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Applied Computer ScienceAGH University of Science and TechnologyKrakówPoland

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