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Managing Light-Signalling Devices in View of City Eco-Logistics

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents the issue of managing the control of vehicle traffic at crossroads by applying classical, traditional methods and a genetic algorithm. While carrying out the research, the authors indicated that genetic operators enable us to control lighting devices more efficiently by about 20% as compared to classical methods and by about 40% compared to traditional methods. Classical methods have been defined as models based on movement sensors only and the FIFO queue whereas the traditional method denotes permanent lighting cycles. Thanks to the elaborated method of controlling the traffic emission of CO2 may be decreased. The paper also indicated further directions for research on methods related to fuzzy sets, neural networks, heuristics and hybrid methods.
Słowa kluczowe
Rocznik
Strony
143--150
Opis fizyczny
Bibliogr. 5 poz., rys.
Twórcy
autor
  • Logistics Institute, Wrocław School of Banking, 53-609 Wrocław, Poland
autor
  • Logistics Institute, Wrocław School of Banking, 53-609 Wrocław, Poland
autor
  • Faculty of Information Technology, Wrocław School of Information Technology, Wrocław, 53-609, Poland
Bibliografia
  • 1. Jacyna M., (2009), Modelling and Evaluation of Transport Systems, Publishing House of Warsaw University of Technology, Warsaw,
  • 2. Markusik S., (2009), Logistic Infrastructure in Transport; v.I. Means of Transport Publishing House of Silesian University of Technology, Gliwice.
  • 3. Topolski M., (2008), Computer Algorithms of Sequential Recognition Combining the Theory of Fuzzy Sets with Dempster-Shafer Theory. PhD dissertation, PRE 01/2008, Wrocław University of Technology, Wrocław.
  • 4. Urban Transport., (2008), Economics and Organization, ed. O. Wyszomirski, Publishing House of Gdańsk Univeristy, Gdańsk.
  • 5. Transport. Transport Problems in enlarged EU (2009), W. Rydzkowski & Wojewódzka- Król (Eds.), PWN Publishing House of, Warsaw 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-edc0e510-5879-4b7e-a650-622183af3592
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