22,413 research outputs found

    Analysis and control of bifurcation and chaos in averaged queue length in TCP/RED model

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    This paper studies the bifurcation and chaos phenomena in averaged queue length in a developed Transmission Control Protocol (TCP) model with Random Early Detection (RED) mechanism. Bifurcation and chaos phenomena are nonlinear behaviour in network systems that lead to degradation of the network performance. The TCP/RED model used is a model validated previously. In our study, only the average queue size k q − is considered, and the results are based on analytical model rather than actual measurements. The instabilities in the model are studied numerically using the conventional nonlinear bifurcation analysis. Extending from this bifurcation analysis, a modified RED algorithm is derived to prevent the observed bifurcation and chaos regardless of the selected parameters. Our modification is for the simple scenario of a single RED router carrying only TCP traffic. The algorithm neither compromises the throughput nor the average queuing delay of the system

    A Vehicular Traffic Flow Model Based on a Stochastic Acceleration Process

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    A new vehicular traffic flow model based on a stochastic jump process in vehicle acceleration and braking is introduced. It is based on a master equation for the single car probability density in space, velocity and acceleration with an additional vehicular chaos assumption and is derived via a Markovian ansatz for car pairs. This equation is analyzed using simple driver interaction models in the spatial homogeneous case. Velocity distributions in stochastic equilibrium, together with the car density dependence of their moments, i.e. mean velocity and scattering and the fundamental diagram are presented.Comment: 27 pages, 6 figure

    Linear chaos for the Quick-Thinking-Driver model

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s00233-015-9704-6In recent years, the topic of car-following has experimented an increased importance in traffic engineering and safety research. This has become a very interesting topic because of the development of driverless cars (Google driverless cars, http://en.wikipedia.org/wiki/Google_driverless_car).Driving models which describe the interaction between adjacent vehicles in the same lane have a big interest in simulation modeling, such as the Quick-Thinking-Driver model. A non-linear version of it can be given using the logistic map, and then chaos appears. We show that an infinite-dimensional version of the linear model presents a chaotic behaviour using the same approach as for studying chaos of death models of cell growth.The authors were supported by a grant from the FPU program of MEC and MEC Project MTM2013-47093-P.Conejero, JA.; Murillo Arcila, M.; Seoane-SepĂșlveda, JB. (2016). Linear chaos for the Quick-Thinking-Driver model. Semigroup Forum. 92(2):486-493. https://doi.org/10.1007/s00233-015-9704-6S486493922Aroza, J., Peris, A.: Chaotic behaviour of birth-and-death models with proliferation. J. Differ. Equ. Appl. 18(4), 647–655 (2012)Banasiak, J., Lachowicz, M.: Chaos for a class of linear kinetic models. C. R. Acad. Sci. Paris SĂ©rie II 329, 439–444 (2001)Banasiak, J., Lachowicz, M.: Topological chaos for birth-and-death-type models with proliferation. Math. Models Methods Appl. Sci. 12(6), 755–775 (2002)Banasiak, J., Lachowicz, M., MoszyƄski, M.: Topological chaos: when topology meets medicine. Appl. Math. Lett. 16(3), 303–308 (2003)Banasiak, J., MoszyƄski, M.: A generalization of Desch–Schappacher–Webb criteria for chaos. Discret. Contin. Dyn. Syst. 12(5), 959–972 (2005)Banasiak, J., MoszyƄski, M.: Dynamics of birth-and-death processes with proliferation–stability and chaos. Discret. Contin. Dyn. Syst. 29(1), 67–79 (2011)Banks, J., Brooks, J., Cairns, G., Davis, G., Stacey, P.: On Devaney’s definition of chaos. Am. Math. Mon. 99(4), 332–334 (1992)Barrachina, X., Conejero, J.A.: Devaney chaos and distributional chaos in the solution of certain partial differential equations. Abstr. Appl. Anal. 457,019, 11 (2012)BermĂșdez, T., Bonilla, A., MartĂ­nez-GimĂ©nez, F., Peris, A.: Li-Yorke and distributionally chaotic operators. J. Math. Anal. Appl. 373(1), 83–93 (2011)Brackstone, M., McDonald, M.: Car-following: a historical review. Transp. Res. Part F 2(4), 181–196 (1999)BrzeĆșniak, Z., Dawidowicz, A.L.: On periodic solutions to the von Foerster–Lasota equation. Semigroup Forum 78, 118–137 (2009)Chandler, R.E., Herman, R., Montroll, E.W.: Traffic dynamics: studies in car following. Op. Res. 6, 165–184 (1958)Chung, C.C., Gartner, N.: Acceleration noise as a measure of effectiveness in the operation of traffic control systems. Operations Research Center. Massachusetts Institute of Technology. Cambridge (1973)CNN (2014) Driverless car tech gets serious at CES. http://edition.cnn.com/2014/01/09/tech/innovation/self-driving-cars-ces/ . Accessed 7 Apr 2014Conejero, J.A., Rodenas, F., Trujillo, M.: Chaos for the hyperbolic bioheat equation. Discret. Contin. Dyn. Syst. 35(2), 653–668 (2015)DARPA Grand Challenge. http://en.wikipedia.org/wiki/2005_DARPA_Grand_Challenge#2005_Grand_Challengede Laubenfels, R., Emamirad, H., Protopopescu, V.: Linear chaos and approximation. J. Approx. Theory 105(1), 176–187 (2000)Desch, W., Schappacher, W., Webb, G.F.: Hypercyclic and chaotic semigroups of linear operators. Ergod. Theory Dyn. Syst. 17(4), 793–819 (1997)El Mourchid, S.: The imaginary point spectrum and hypercyclicity. Semigroup Forum 73(2), 313–316 (2006)El Mourchid, S., Metafune, G., Rhandi, A., Voigt, J.: On the chaotic behaviour of size structured cell populations. J. Math. Anal. 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    "0-1" test chaosu

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    The goal of this thesis is to research the 0-1 test for chaos, its application in Matlab, and testing on suitable models. Elementary tools of the dynamical systems analysis are introduced, that are later used in the main results part of the thesis. The 0-1 test for chaos is introduced in detail, defined, and implemented in Matlab. The application is then performed on two one-dimensional discrete models where the first one is in explicit and the second one in implicit form. In both cases, simulations in dependence of the state parameter were done and main results are given - the 0-1 test for chaos, phase, and bifurcation diagrams.HlavnĂ­m cĂ­lem bakaláƙskĂ© prĂĄce je studium 0-1 testu chaosu, jeho implementace v Matlabu a nĂĄslednĂ© testovĂĄnĂ­ na vhodnĂœch modelech. V prĂĄci jsou zavedeny zĂĄkladnĂ­ nĂĄstroje analĂœzy dynamickĂœch systĂ©mĆŻ, kterĂ© jsou později pouĆŸity v části hlavnĂ­ch vĂœsledkĆŻ. 0-1 test chaosu je podrobně uveden, ƙádně definovĂĄn a implementovĂĄn v Matlabu. Aplikace je provedena na dvou jednodimenzionĂĄlnĂ­ch diskrĂ©tnĂ­ch modelech z nichĆŸ jeden je v explicitnĂ­m a druhĂœ v implicitnĂ­m tvaru. V obou pƙípadech byly provedeny simulace v zĂĄvislosti na stavovĂ©m parametru a hlavnĂ­ vĂœsledky byly demonstrovĂĄny formou 0-1 testu chaosu, fĂĄzovĂœch a bifurkačnĂ­ch diagramĆŻ.470 - Katedra aplikovanĂ© matematikyvĂœborn

    Empirical exploration of air traffic and human dynamics in terminal airspaces

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    Air traffic is widely known as a complex, task-critical techno-social system, with numerous interactions between airspace, procedures, aircraft and air traffic controllers. In order to develop and deploy high-level operational concepts and automation systems scientifically and effectively, it is essential to conduct an in-depth investigation on the intrinsic traffic-human dynamics and characteristics, which is not widely seen in the literature. To fill this gap, we propose a multi-layer network to model and analyze air traffic systems. A Route-based Airspace Network (RAN) and Flight Trajectory Network (FTN) encapsulate critical physical and operational characteristics; an Integrated Flow-Driven Network (IFDN) and Interrelated Conflict-Communication Network (ICCN) are formulated to represent air traffic flow transmissions and intervention from air traffic controllers, respectively. Furthermore, a set of analytical metrics including network variables, complex network attributes, controllers' cognitive complexity, and chaotic metrics are introduced and applied in a case study of Guangzhou terminal airspace. Empirical results show the existence of fundamental diagram and macroscopic fundamental diagram at the route, sector and terminal levels. Moreover, the dynamics and underlying mechanisms of "ATCOs-flow" interactions are revealed and interpreted by adaptive meta-cognition strategies based on network analysis of the ICCN. Finally, at the system level, chaos is identified in conflict system and human behavioral system when traffic switch to the semi-stable or congested phase. This study offers analytical tools for understanding the complex human-flow interactions at potentially a broad range of air traffic systems, and underpins future developments and automation of intelligent air traffic management systems.Comment: 30 pages, 28 figures, currently under revie
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