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Design and development of a road traffic redirection system

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Języki publikacji
EN
Abstrakty
EN
Nowadays, the crucial issue of guidance systems based on a GPS signal is that they are not able to redirect road users, taking into account the current state of traffic (and the predicted state within the time of the travel) in the city. In this paper we present a three layer architecture of a computer system capable of redirecting users of an urban road system via routes with a lighter traffic load in order to reach their declared destination in the city. A basic layer is a multiprocessor calculation server running Dijkstra path search tasks, the middle layer - the one which is visible to the road user - is a replicable proxy server that collects route requests from road users. The third layer is a mobile application. The prototype of such a system was developed by the ArsNumerica Group. The crucial feature of the system is feedback from road users that allows us to adjust the whole Intelligent Transportation System in the city to changes in traffic flow at various road links introduced by the redirection process applied to many users. The performance test strategy to prove the efficiency of the architecture was carried out for the city of Wrocław.
Rocznik
Strony
3--8
Opis fizyczny
Bibliogr. 21
Twórcy
autor
  • WROCŁAW UNIVERSITY OF SCIENCE AND TECHNOLOGY, Faculty of Electronics, ul. Janiszewskiego 11/17, 50-372 Wrocław
autor
  • WROCŁAW UNIVERSITY OF SCIENCE AND TECHNOLOGY, Faculty of Electronics, ul. Janiszewskiego 11/17, 50-372 Wrocław
autor
  • WROCŁAW UNIVERSITY OF SCIENCE AND TECHNOLOGY, Faculty of Electronics, ul. Janiszewskiego 11/17, 50-372 Wrocław
autor
  • WROCŁAW UNIVERSITY OF SCIENCE AND TECHNOLOGY, Faculty of Electronics, ul. Janiszewskiego 11/17, 50-372 Wrocław
autor
  • WROCŁAW UNIVERSITY OF SCIENCE AND TECHNOLOGY, Faculty of Electronics, ul. Janiszewskiego 11/17, 50-372 Wrocław
Bibliografia
  • [1] BAZAN M., et al.: Multithreaded enhancements of the Dijkstra algorithm for route optimization in urban networks, Archives on Transport Systems Telematics, Vol. 9, Issue 2, 2016, pp. 3-7.
  • [2] CORMEN, T. H., et. al.: Introduction to Algorithms. MIT Press, 2nd edition, 2001.
  • [3] SCHRIJVER, A.: Combinatorial Optimization — Polyhedra and Efficiency. Algorithms and Combinatorics 24. Springer. ISBN 3-540-20456-3, vol. A, sect.7.5b, p.103, 2004.
  • [4] BAUER, R.: On the Complexity of Partitioning Graphs for Arc-Flags, Journal of Graph Algorithms and Applications, vol. 17, no. 3, 2013, pp. 265–299.
  • [5] ZHAN, F.B., NOON, C.E.: Shortest Path Algorithms: An Evaluation using Real Road Networks. Transp. Sci., 32, 1998, pp. 65–73.
  • [6] KOZYNTSEV, A.N.: www14.informatik.tu-muenchen.de/ lehre/2010SS/sarntal/07_kozyncev_slides.pdf, Facultat fur Informatic, TU Munchen, 2010, [date of access: 26.02.2016].
  • [7] ERINLE, B.: JMeter Cookbook, Packt, 2014.
  • [8] https://www.tomtom.com/ [date of access: 27.02.2017].
  • [9] http://www.automapa.pl/pl/start/ [date of access: 27.02.2017].
  • [10] http://maps.google.com [date of access: 27.02.2017].
  • [11] MAGED, M., et. al.: Scale-up x Scale-out: A Case Study using Nutch/Lucene. 2007 IEEE International Parallel and Distributed Processing Symposium. p. 1. doi:10.1109/ IPDPS.2007.370631 [date of access: 26.03.2007].
  • [12] HELBING, D.: Derivation of a fundamental diagram for urban traffic flow, The European Physical Journal B, July 2009, Volume 70, Issue 2, pp 229-241.
  • [13] PETZOLD, Ch.: Creating Mobile Apps with Xamarin.Forms, Microsoft 2015.
  • [14] SZYMAŃSKI, A., et al.: Two methods of calculation of the origination destination matrix of an urban area, Raport W04/P-007/15, Wrocław University of Technology, 2015.
  • [15] Biuro inżynierii transportu, Pentor Research International, Kompleksowe Badania Ruchu - Wrocław 2010, (in Polish).
  • [16] WHITE, T.: Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale, 4th Edition, O’Reilly, 2015.
  • [17] DUBOIS, P.: MySQL (5th Edition) (Developer’s Library), Addison-Wesley, 2013. [18] OWENS, M., ALEN, G.: The Definitive Guide to SQLite, Apress, 2010.
  • [19] DAS, S.: SQLite for Mobile Apps Simplified, Amazon, 2014.
  • [20] HALAWA, K., et al.: Road traffic predictions across major city intersections using multilayer perceptrons and data from multiple intersections located in various places, IET Intelligent Transport Systems 10 (7), 469-475, 2016.
  • [21] CISKOWSKI P., et al.: Estimation of travel time in the city based on intelligent transportation system traffic data with the use of neural networks, Dependability Engineering and Complex Systems, 85-95, 2016.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-86662dcd-32f1-4a86-b7fc-4bc76ac22271
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