Modeling and Optimization of Traffic Flow in Urban Areas - Czech ...

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70 Bibliography[Cast 96][Chre 89][Chre 95]D. J. M. Castillo. “A car-following model based on the Lighthill-Whitham Theory”. In: J. Lesort, Ed., Proceedings of the 13thInternational Symposium of Transportation and Traffic Theory,pp. 517–538, 1996.P. Chrétienne. “A Polynomial Algorithm to Optimally ScheduleTasks on a Virtual Distributed System under Tree-like PrecedenceConstraints”. European Journal of Operational Research, Vol. 43,No. 43, pp. 225–230, 1989.P. Chrétienne, E. G. Coffman, J. K. Lenstraand, and Z. Liu.Scheduling theory and its applications. John Wiley & Sons Ltd,Baffins Lane, Chichester, West Sussex PO19 1UD, England, 1995.[Cram 06] Y. Crama and P. L. Hammer. “Boolean Functions: Theory, Algorithmsand Applications”. 2006.http://www.rogp.hec.ulg.ac.be/Crama/Publications/BookPage.html.[Davi 01][Davi 04][Davi 98][Diak 02][Febb 01][Febb 04]R. David and H. Alla. “On Hybrid Petri Nets”. Discrete EventDynamic Systems, Vol. 11, No. 1-2, pp. 9–40, 2001.R. David and H. Alla. Discrete, Continuous, and Hybrid PetriNets. Springer, November 23 2004.R. David and H. Alla. “A modeling and analysis tool for discreteevents systems: continuous Petri net”. Performance Evaluation,Vol. 33, pp. 175–199, 1998.C. Diakaki, M. Papageorgiou, and K. Aboudolas. “A multivariableregulator approach to traffic-responsive network wide signalcontrol”. Control Engineering Practice, Vol. 10, No. 2, pp. 183–195, February 2002.A. D. Febbraro, D. Giglio, and N. Sacco. “Modular representationof urban traffic systems based on hybridPetri nets”. In: IntelligentTransportation Systems, pp. 866–871, Oakland, CA, USA, 2001.A. D. Febbraro, D. Giglio, and N. Sacco. “Urban traffic controlstructure based on hybrid Petri nets”. IEEE Transactions onIntelligent Transportation Systems, Vol. 5, pp. 224–237, 2004.
Bibliography 71[Febb 06] A. D. Febbraro and D. Giglio. “Urban traffic control in modular/switchingdeterministic-timed Petri nets”. In: 11th IFACSymposium on Control in Transportation Systems, 2006.[Figu 01]L. Figueiredo, I. Jesus, J. Machado, J. Ferreira, and J. Santos.“Towards the development of intelligent transportation systems”.In: IEEE Intelligent Transportation Systems Proceedings, p. 29,2001.[Find 02] R. Findeisen and F. Allgöwer. “An Introduction to NonlinearModel Predictive Control”. In: 21st Benelux Meeting on Systemsand Control, March 2002.[Gart 83]N. H. Gartner. “OPAC: A demand-responsive strategy for trafficsignal control”. Transportation Research Record, Vol. 906, pp. 75–81, 1983.[Gazi 02] D. C. Gazis. Traffic theory. Kluwer, 2002.[Gazi 63]D. C. Gazis and R. Potts. “The oversaturated intersection”. In:Proc. 2nd Int. Symp. Traffic Theory, pp. 221–237, 1963.[Gonz 08] M. Gonzalez et al. “MAST (Modeling and Analysis Suite forReal-Time Applications)”. http://mast.unican.es/, 2008.[Goog 09] Google. “Prague Google Maps”. http://maps.google.com/, December2009.[Groo 92]S. H. de Groot, S. Gerez, and O. Herrmann. “Range-chart-guidediterative data-flow graph scheduling”. Circuits and Systems I:Fundamental Theory and Applications, IEEE Transactions on,Vol. 39, pp. 351–364, 1992.[Gube 08] S. Guberinić, G. Šenborn, and B. Lazić. Optimal Traffic Control:Urban Intersections. CRC Press, 6000 Broken Sound ParkwayNW, Suite 300, Boca Raton, 2008.[Haef 98]L. E. Haefner and M.-S. Li. “Traffic Flow Simulation for an UrbanFreeway Corridor”. Transportation Conference Proceedings, 1998.
Page 1 and 2:
Czech Technical University in Pragu
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This thesis is dedicated to my wife
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Nomenclatureα|β|γ Graham and B̷
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NomenclatureviiR 0+ set of non-nega
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AbbreviationsCCPN Constant speed Co
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Goals and ObjectivesThis thesis wil
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ContentsGoals and Objectivesxi1 Int
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List of Tables2.1 Traffic data for
Page 19 and 20:
Chapter 1IntroductionThe urban traf
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1.1 Related Work 3Traffic stream mo
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Chapter 2Simple Light ControledInte
Page 25 and 26:
2.2 Extended Queue Model 72 E( k)AB
Page 27 and 28:
2.2 Extended Queue Model 9E [s]4000
Page 29 and 30:
2.4 Control of The Simple Intersect
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38: Chapter 3General Light ControlledIn
Page 39 and 40: 3.2 Continuous Petri Net 21take the
Page 41 and 42: 3.2 Continuous Petri Net 23v 5V 5vD
Page 43 and 44: 3.3 Light Controlled Intersection M
Page 49 and 50: 3.4 Performance Evaluation 31-1V[uv
Page 51 and 52: 3.4 Performance Evaluation 33-1V [u
Page 53 and 54: Chapter 4TORSCHE SchedulingToolbox
Page 55 and 56: 4.2 Tool Architecture and Basic Not
Page 63 and 64: 4.3 Implemented Algorithm 45tasks a
Page 65 and 66: 4.3 Implemented Algorithm 47leg 1p=
Page 67 and 68: 4.3 Implemented Algorithm 49unit j
Page 69 and 70: 4.3 Implemented Algorithm 51P 2P 1
Page 71 and 72: Chapter 5Traffic Flow OptimizationT
Page 73 and 74: 5.2 Traffic Region Model 5514 1516
Page 75 and 76: 5.3 Tasks Definition for Intersecti
Page 77 and 78: 5.4 Scheduling with Communication D
Page 79: 5.5 Summary 61Intersection 6T 2,6T
Page 82 and 83: 64 Chapter 6 Conclusionsoptimal und
Page 85 and 86: Appendix ATORSCHE AlgorithmsA.1 Sch
Page 87: Bibliography[Abou 09] K. Aboudolas,
Page 91 and 92: Bibliography 73[Kwak 72]Cybernetics
Page 93: Bibliography 75[Tolb 01] C. Tolba.
Page 96 and 97: 78 Indexphase, 3offset, 3, 53split,
Page 99 and 100: List of Author’s PublicationsPape
Page 101: List of Author’s Publications 83P
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