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

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74 Bibliographyin Computers and Processors, p. 395, IEEE Computer Society,Washington, DC, USA, 2002.[Mosk 01] M. W. Moskewicz, C. F. Madigan, Y. Zhao, L. Zhang, and S. Malik.“Chaff: Engineering an Efficient SAT Solver”. In: Proceedingsof the 38th Design Automation Conference (DAC’01), pp. 530–535, ACM, 2001.[Muni 09] A. C. Muniyappa. Computer Safety, Reliability, and Security.Springer, Berlin Heidelberg, 2009.[Naga 07][Nage 03][Papa 03][Pine 02]T. Nagatani. “Vehicular traffic through a sequence of green-wavelights”. Physica A: Statistical Mechanics and its Applications,Vol. 380, pp. 503 – 511, 2007.K. Nagel, P. Wagner, and R. Woesler. “Still flowing: Approachesto traffic flow and traffic jam modeling”. Operations research,Vol. 51, No. 5, pp. 681–710, 2003.M. Papageorgiou, C. Diakaki, V. Dinopoulou, A. Kotsialos, andY. Wang. “Review of Road Traffic Control Strategies”. PRO-CEEDINGS - IEEE, Vol. 91, pp. 2043–2067, 2003.M. Pinedo et al. LEKIN R○ - Flexible Job-Shop Scheduling System.New York University, Leonard N. Stern School of Business NewYork, NY, 2002.http://www.stern.nyu.edu/om/software/lekin/.[Pine 08] M. Pinedo. Scheduling: Theory, Algorithms, and Systems.Springer, 233 Spring Street, NewYork, NY 10013, USA, thirdEd., 2008.[Prag 09]Prague city. “Statistika registru silničních vozidel v hl.m. Praze”.http://doprava.praha-mesto.cz/, December 2009.[Robe 69] D. Robertson. “TRANSYT method for area traffic control”. TrafficEng. Control, Vol. 10, p. 276, 1969.[Sen 97]S. Sen and L. K. Head. “Controlled Optimization of Phases at anIntersection”. Transportation Science, Vol. 31, pp. 5–17, 1997.
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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
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Chapter 1IntroductionThe urban traf
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1.1 Related Work 3Traffic stream mo
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Chapter 2Simple Light ControledInte
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2.2 Extended Queue Model 72 E( k)AB
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2.2 Extended Queue Model 9E [s]4000
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2.4 Control of The Simple Intersect
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Chapter 3General Light ControlledIn
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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 and 88: Bibliography[Abou 09] K. Aboudolas,
Page 89 and 90: Bibliography 71[Febb 06] A. D. Febb
Page 91: Bibliography 73[Kwak 72]Cybernetics
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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