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Modelling of expected traffic smoothness in urban transportation systems for ITS solutions

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In urban networks, with dense traffic flows and a high risk of the disruption (even in the form of a short queue of vehicles) the probability of occurrence of such a situation (disruption and queue) is a better measure of the probabilistic description of the capacity constraints than the expected waiting time in the queue, because the probability takes into account the risk of delay in the traffic flow from the point of view of the person that plans a trip. The functions of expected smoothness of the traffic flows in the elementary nodes and the expected waiting time in the queue for different packages of ITS services have been presented in the mathematical forms.
Rocznik
Strony
33--45
Opis fizyczny
Bibliogr. 51 poz., rys., wykr.
Twórcy
autor
  • Silesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, Poland
  • Silesian University of Technology, Faculty of Transport, Department of Transportation Systems and Traffic Engineering, Katowice, Poland
Bibliografia
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  • [13] IZDEBSKI, M., 2014. The Use of Heuristic Algorithms to Optimize the Transport Issues on the Example of Municipal Services Companies. Archives of Transport, 29(1), pp. 27-36.
  • [14] JACYNA, M. and MERKISZ, J., 2014. Proecological approach to modelling traffic organization in national transport system. Archives of Transport, 30(2), pp. 31-41.
  • [15] JACYNA, M., 1999. Multicriteria evaluation of traffic flow distribution in a multimodal transport corridor, taking into account logistics base service. Archives of Transport, 11(3-4), pp. 43-66.
  • [16] JACYNA, M., 2009. Modelowanie i ocena systemów transportowych. Warsaw: Oficyna Wydawnicza Politechniki Warszawskiej.
  • [17] JACYNA, M., WASIAK, M., LEWCZUK, K. and KŁODAWSKI, M., 2014. Simulation model of transport system of Poland as tool for developing sustainable transport. Archives of Transport, 31(3), pp. 23-35.
  • [18] JACYNA-GOŁDA, I., ŻAK, J. and GOŁĘBIOWSKI, P., 2014. Models of traffic flow distribution for various scenarious of the development of proecological transport system. Archives of Transport, 32(4), pp. 17-28.
  • [19] JANECKI, R. and KAROŃ, G., 2014. Concept of Smart Cities and Economic Model of Electric Buses Implementation. In: J. MIKULSKI, ed, Telematics-Support for Transport. Springer Berlin Heidelberg, pp. 100-109.
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  • [21] KAROŃ, G. and MIKULSKI, J., 2011b. Transportation Systems Modelling as Planning, Organisation and Management for Solutions Created with ITS. In: J. MIKULSKI, ed., Modern Transport Telematics. Springer Berlin Heidelberg, pp. 277-290.
  • [22] KAROŃ, G. and MIKULSKI, J., 2012. Problems of ITS Architecture Development and ITS architecture implementation in Upper-Silesian Conurbation in Poland. In: J. MIKULSKI, ed, Telematics in the Transport Environment. Springer Berlin Heidelberg, pp. 183-198.
  • [23] KAROŃ, G. and MIKULSKI, J., 2014. Problems of Systems Engineering for ITS in Large Agglomeration–Upper-Silesian Agglomeration in Poland. In: J. MIKULSKI, ed., Telematics-Support for Transport. Springer Berlin Heidelberg, pp. 242-251.
  • [24] KAROŃ, G., 2013. Travel Demand and Transportation Supply Modelling for Agglomeration without Transportation Model. In: J. MIKULSKI, ed., Activities of Transport Telematics. Springer Berlin Heidelberg, pp. 284-293.
  • [25] KAROŃ, G., SOBOTA, A. et al., 2014. Analysis of the existing transport systems in the Upper-Silesian Agglomeration on the basis of quantitative and qualitative surveys. Katowice: Silesian Cluster of Urban Transport – Centre of Transport Development.
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  • [27] MERKISZ, J., JACYNA, M., MERKISZ-GURANOWSKA, A. and PIELECHA, J., 2014. The parameters of passenger cars engine in terms of real drive emission test. The Archives of Transport, 32(4), pp. 43-50.
  • [28] MERKISZ-GURANOWSKA, A. and PIELECHA, J., 2014. Passenger cars and heavy duty vehicles exhaust emissions under real driving conditions. Archives of Transport, 31(3), pp. 47-59.
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  • [30] OSORIO, C. and BIERLAIRE, M., 2009. A surrogate model for traffic optimization of congested networks: an analytic queueing network approach. TRANSP-OR 090825. Switzerland: EcolePolytechniqueF´ed´erale de Lausanne.
  • [31] PYZA, D., 2008. Selected aspects of modelling of conveyance systems at random supply. Archives of Transport, 20(3), pp. 47-61.
  • [32] PYZA, D., 2009. Optimisation of transport in distribution systems with restrictions on delivery times. Archives of Transport, 21(3-4), pp. 125-147.
  • [33] PYZA, D., 2011. Multi-criteria evaluation of transportation systems in supply chains. Archives of Transport, 23(1), pp. 47-65.
  • [34] SZARATA, A., 2014. The multimodal approach to the modelling of modal split. Archives of Transport, 29(1), pp. 55-63.
  • [35] SZCZEPAŃSKI, E., JACYNA-GOŁDA, I. and MURAWSKI, J., 2014. Genetic algorithms based approach for transhipment hub location in urban areas. Archives of Transport, 31(3), pp. 73-83.
  • [36] TOMANEK, R., JANECKI, R., KAROŃ, G. and ET AL, 2013. Strategy of development for central subregion of Silesia in the years 2014-2020 and programme of action for Integrated Territorial Investments. University of Economics in Katowice: The Research and Expertise Centre.
  • [37] WASIAK, M., 2007. A queuing theory approach to logistics systems modelIing. Archives of Transport, 19(3), pp. 103-120.
  • [38] WASIAK, M., 2009. Simulation model of logistic system. Archives of Transport, 21(3-4), pp. 189-206.
  • [39] WASIAK, M., 2011. Formal notation of a logistic system model taking into consideration cargo stream transformations. Archives of Transport, 23(1), pp. 91-110.
  • [40] WNUK, D. and KAROŃ, G., 2014. Variants to improve traffic conditions in the bottleneck in Road Network of the Upper-Silesian Conurbation, Conference Proceedings on CD-ROM VI International Scientific Conference „Transport Problems 2014”, 25-27 June 2014, pp. 970-981.
  • [41] WOCH, J., 1999. Two queueing theory models for traffic flow. Archives of Transport, 11(1-2), pp. 73-90.
  • [42] WOCH, J., 2004. Delay functions and freedom functions. Archives of Transport, 16(1), pp. 71-86.
  • [43] WOLFENBURG, A., 2014. New version of the BBS method and its usage for determining and scheduling vehicle routes. Archives of Transport, 31(3), pp. 83-91.
  • [44] ŻOCHOWSKA, R. and KAROŃ, G., 2016. ITS Services Packages as a Tool for Managing Traffic Congestion in Cities. In: A. SŁADKOWSKI and W. PAMUŁA, eds, Intelligent Transportation Systems–Problems and Perspectives. Springer International Publishing, pp. 81-103.
  • [45] ŻOCHOWSKA, R. and Sobota, A., 2014. Fundamentalny diagram ruchu – teoria i praktyka. Logistyka, 2014(6), pp. 11862-11871.
  • [46] ŻOCHOWSKA, R., 2011. Modele wyboru drogi wykorzystywane w budowie dynamicznych macierzy podróży. Logistyka, 2011(4), pp. 1026-1036.
  • [47] ŻOCHOWSKA, R., 2012. Dynamic approach to the origin-destination matrix estimation in dense street networks. Archives of Transport, 24(3), pp. 389-413.
  • [48] ŻOCHOWSKA, R., 2014a. Improvement of traffic safety in road work zones. Logistyka, 2014(4), pp. 3459-3467.
  • [49] ŻOCHOWSKA, R., 2014b. Niekonwencjonalne metody wyznaczania rozkładu przestrzennego ruchu. Logistyka, 2014(6).
  • [50] ŻOCHOWSKA, R., 2014c. Safety in road work zone – practical aspects. Logistyka, 2014(4), pp. 3469-3478.
  • [51] ŻOCHOWSKA, R., 2014d. Selected Issues in Modelling of Traffic Flows in Congested Urban Networks. Archives of Transport, 29(1), pp. 77-89.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b6603143-a11b-4c06-9b77-435bd71c3922
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