DepCoS-RELCOMEX 2016: Dependability Engineering and Complex Systems pp 409-418 | Cite as

The Issue of Analyzing Measurement Data of Driving Speed in Large Urban Areas

Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 470)

Abstract

The measurement of speed is the subject of analysis and publication of many researchers around the world. This issue is analyzed from the point of view of movement engineering, urban planning, logistics, but also the city management. The researches, initiated by the authors in this paper, are focused on measuring the time of vehicle journeys on the selected section of one of the main streets of Wroclaw. The aim of the chapter is to present the issues related to the analysis of measurement data from the ITS, which are aimed at supporting decision-making processes of those responsible for organizing transport in the city. For this purpose, the authors presented the basic theoretical issues of the study area and the approximate principles of operation of ITS systems. Then on the basis of quantitative analysis, the authors characterized the difficulties that may be encountered while drawing conclusions from the analysis of the collected data.

Keywords

Movement engineering Data analyzing ITS 
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Birr, K., Jamroz, K., Kustra, W.: Travel time of public transport vehicles estimation. Transportation Research Procedia 3, 359–365 (2014)CrossRefGoogle Scholar
  2. 2.
    Datka, S., Tracz, M.: Przewodnik do ćwiczeń z inżynierii ruchu. Politechnika Krakowska, Kraków (1974)Google Scholar
  3. 3.
    Datka, S., Suchorzewski, W., Tracz, M.: Inżynieria ruchu. WKŁ, Warszawa (1999)Google Scholar
  4. 4.
    European Commission: MASTER Managing speeds of traffic on European roads (No. RO-96-SC.202). European Commission, Finland (1999)Google Scholar
  5. 5.
    Freedman, D.A.: Ecological inference and the ecological fallacy. Int. Encycl. Soc. Behav. Sci. 6, 4027–4030 (1999)Google Scholar
  6. 6.
    Gaca, S., Suchorzewski, W., Tracz, M.: Inżynieria ruchu drogowego: teoria i praktyka. WKŁ, Warszawa (2014)Google Scholar
  7. 7.
    Hadas, A.: Zastosowanie zintegrowanego systemu transportu w aglomeracji miejskiej. Przegląd Komunikacyjny 4, 8–13 (2015)Google Scholar
  8. 8.
    Kempa, J., Szczuraszek, T.: Design speed, actual speed and road designing. In: 2nd International Symposium on Highway Geometric Design. Transportation Research Board, Road and Transportation Research Association, Mainz, German (2000)Google Scholar
  9. 9.
    Kierzkowski, A., Kisiel, T.: The simulation model of logistic support for functioning ground handling agent, taking into account the probabilistic time of aircrafts arrival. In: Carpathian Logistics Congress—Congress Proceedings, pp: 463–469 (2013)Google Scholar
  10. 10.
    Oskarbski, J., Jamroz, K., Litwin, M.: Inteligentne systemy transportu– zaawansowane systemy zarządzania ruchem. www.pkd.org.pl/pliki/referaty/oskarbski,_jamroz,_litwin.pdf. Accessed January 2016
  11. 11.
    Park, Y., Saccomanno, F.: Evaluating speed consistency between successive elements of a two-lane rural highway. Transp. Res. Part A: Policy Pract. 40, 375–385 (2006)Google Scholar
  12. 12.
    Restel, F.J.: Train punctuality model for a selected part of railway transportation system. In: Safety, Reliability and Risk Analysis: Beyond the Horizon—Proceedings of the European Safety and Reliability Conference (2014)Google Scholar
  13. 13.
    Shinar, D.: Traffic Safety and Human Behavior. Elsevier, Oxford (2007)CrossRefGoogle Scholar
  14. 14.
    Szczuraszek, T.: Prędkość pojazdów w warunkach drogowego ruchu swobodnego. Komitet Inżynierii Lądowej i Wodnej PAN, Warszawa (2008)Google Scholar
  15. 15.
    Watanatada, T.: A Model for Predicting Free-flow Speed Based on Probabilistic Limiting Velocity Concepts: Theory and Estimation. Transportation Research Record, vol. 1091 (1986)Google Scholar
  16. 16.
    Zhang, J., Wang, F.Y., Wang, K., Lin, W.H., Xu, X., Chen, C.: Data-driven intelligent transportation systems: a survey. IEEE Trans. Intel. Transp. Syst. 12(4), 1624–1639 (2011)CrossRefGoogle Scholar
  17. 17.
    www.itspolska.pl. Accessed January 2016
  18. 18.

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Wroclaw University of TechnologyWroclawPoland

Personalised recommendations