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

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42 Chapter 4 TORSCHE Scheduling Toolbox for Matlabsd Scheduling Part of Toolbox Usesimple taskset definitioncomplex taskset definitionsd Create Taskset 1taskset()loop:Tasksettask()user at Matlabcommand line:Tasksd Create Taskset 2loop task():Tasktaskset():Tasksetsd Classificationsd Scheduling Algorithmproblem():Problemvalid input instancesinvalid inputinstancessd Read Propertiessd Schedulingalgorithmname()AlgorithmAlgorithm :Tasksetget()loop get():TaskrefSchedulingAlgorithmsd Gantt Chart:Tasksetplot()loopplot()no-exist schedule:TaskrefScheduling Algorithm Solversd Schedule to the TasksAlgorithm :Taskset :Taskadd schedule()loop add scht()Fig. 4.3: UML Interaction Overview Diagram of a typical toolbox work-flow of thescheduling problem solution
4.2 Tool Architecture and Basic Notation 43Fig. 4.4: Graphedit (main window, library browser, property editor)The toolbox is equipped with a simple but powerful editor of graphs calledGraphedit based on the System Handle Graphics of Matlab. It allows one toconstruct directed graphs with various user parameters on nodes and edges bysimple and an intuitive way. Fig. 4.4 shows the Graphedit with a graph withvarious graphical representations of nodes, various edge paths and two settingwindows: property editor and node library. The constructed graph can beeasily used to create an instance of the class Graph which can be exported tothe Matlab workspace or saved to a binary mat-file. In addition, Grapheditcontains a system of plug-ins which allow one to extend its functionality bythe user.Moreover, due to the close relationship between the scheduling and graphalgorithms, each object Graph can be transformed to an object Taskset andvice versa. Obviously, the nodes from the graph are transformed to the tasksin the Taskset and the edges are transformed to the precedence constraintsand vice versa according to the user specification.
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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
Page 9 and 10: AbbreviationsCCPN Constant speed Co
Page 11 and 12: Goals and ObjectivesThis thesis wil
Page 13 and 14: ContentsGoals and Objectivesxi1 Int
Page 17 and 18: List of Tables2.1 Traffic data for
Page 19 and 20: Chapter 1IntroductionThe urban traf
Page 21 and 22: 1.1 Related Work 3Traffic stream mo
Page 23 and 24: 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 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 57 and 58: 4.2 Tool Architecture and Basic Not
Page 59: 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 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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