Advertisement

Using Computer Methods to Identify the Factors Affecting the Management of an Urban Parking Lot

Conference paper
  • 673 Downloads
Part of the Eurasian Studies in Business and Economics book series (EBES, volume 2/2)

Abstract

As the growth of urban areas continues, the area previously used as parking space begins to shrink significantly. For that reason, the only way to increase the parking capacity in cities is to construct more multi-story parking lots. Direct correlation of social, environmental and economic factors sets the way of parking lot planning and design basing on sustainable development principle. The article describes the variables that influence the parking lot management model and presents computer methods that can be used to identify the factors affecting it. The measurements of traffic intensity at the entrance and exit of a shopping centre in Wroclaw are also included. The developmental nature of this project requires that certain problems to be analyzed more closely.

Keywords

Parking traffic management Reverse logistics Motorization index Urban parking Traffic intensity Driver decision-making Genetic algorithms Dempster-Shafer theory Fuzzy sets 

References

  1. Appelt, K. C., Milch, K. F., Handgraaf, M. J. J., & Weber, E. U. (2011). The decision making individual differences inventory and guidelines for the study of individual differences in judgment and decision-making research. Judgment and Decision Making, 6(3), 252–262.Google Scholar
  2. Burdzinski, J. (2012). Car park—The positive component of the landscape. Prace Komisji Krajobrazu Kulturalnego, 18, 21–31.Google Scholar
  3. Charlan, J. N. (2012). The psychological basis of quality decision making (IRLE Working 128-12). [online] Accessed August 30, 2013, from http://irle.berkeley.edu/workingpapers/128-12.pdf
  4. Gradkowski, K. (2009). Wielopoziomowe budowle parkingów w dużych miastach [Multilevel parking buildings in large cities]. Przegladkomunikacyjny, 4/209, 41–47.Google Scholar
  5. Jaracz, M., & Borkowska, A. (2010). Decision making in context of neurobiological research and psychological theories. Psychiatry, 7(2), 68–74.Google Scholar
  6. Korzen, Z. (2001). Ekologistyka [Green logistics]. Poznań: Biblioteka logistyka.Google Scholar
  7. Menneer, T., Donnelly, N., Godwin, H. J., & Cave, K. R. (2010). High or low target prevalence increases the dual-target cost in visual search. Journal of Experimental Psychology, 16(2), 133–144.PubMedGoogle Scholar
  8. Rozporządzenie Ministra Infrastruktury. (2002). w sprawie warunków technicznych, jakim powinny odpowiadać budynki i ich usytuowanie [Regulation of the Ministerof Infrastructure, 2002 on technical conditionsto be met by buildings and their location] (Dz. U. Nr 75, poz. 690). [online] Accessed August 30, 2010, from http://isap.sejm.gov.pl/Download;jsessionid=879C7B5979C1755527637401A8B6D306?id=WDU20020750690&type=2
  9. Statistical Information and Elaborations. (2013). Transport. Activity results in 2012. Polish Central Statistical Office. [online] Accessed August 30, 2013, from http://old.stat.gov.pl/cps/rde/xbcr/gus/tc_transport_activity_results_in_2012.pdf
  10. Szczepaniak, C. (2000). Samochód na przełomie epok [The carat the end ofthe ages]. Łódź: PWN Warszawa.Google Scholar
  11. Szoltysek, J. (2007). Podstawy logistyki miejskiej [Fundamentals of urban logistics]. Katowice: Wyd. Akademii Ekonomicznej w Katowicach.Google Scholar
  12. Topolski, M. (2008). Komputerowealgorytmy rozpoznawania sekwencyjnego łączące teorię zbiorów rozmytych z teorią Dempstera-Shafera [Komputerowe algorytmy recognition sequence linking the theory of fuzzy sets theory, Dempster-Shafer]. Ph.D. PRE 01/2008, Wroclaw University of Technology. Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute LogisticWroclaw School of BankingWroclawPoland
  2. 2.Ove Arup & Partners International Ltd. Sp z o.o. Oddział w PolsceWarszawaPoland
  3. 3.International University of Logistics and Transport in WroclawWroclawPoland

Personalised recommendations