MODELING OF TRAFFIC ON FAIRWAYS OPTIMIZING THE ALLOCATION OF TRAFFIC by Quirine de Kloet in partial fulfillment of the requirements for the degree of Master of Science in Applied Mathematics at the Delft University of Technology, to be defended publicly on 9th of December 2016. Student number: 4148517 Specialisation: Computational Science and Engineering Faculty: EEMCS An electronic version of this thesis is available at http://repository.tudelft.nl/. PREFACE As the last element of my masters in Applied Mathematics I have completed my graduation project at Rijk- swaterstaat. This is the executive agency of the Ministry of Infrastructure and the Environment; this agency works on keeping the Netherlands safe, habitable and accessible. In order to reach this goal Rijkswaterstaat manages and develops the main road network, the main fairway network and the main water system in the Netherlands.[1] While there has been a lot of research into traffic on roads, traffic on fairways has been largely neglected. Within the Netherlands there are 3431 kilometers of inland fairways while there are only 3058 kilometers of highway. This is not even taking into account the 3523 kilometers of maritime routes on the North Sea, Wadden Sea and IJselmeer.[1] When one six barge convoy is used (a ship pushing six barges) this saves 660 trucks traveling on the road. Optimizing the use of fairways can diminish the traffic jams on roads. In order to give the fairways their much deserved research I have dedicated my graduation project to investigating the traffic on fairways. After a broad investigation of fairways and fairway traffic the subject of my thesis was specified to modeling fairway traffic. I am glad to have been able to do my graduation project investigating such an interesting topic. I would like to thank my daily supervisor Krystyna Robaczewska for all the help and guidance she has given me during this project. I would also like to thank my academic supervisors Arnold Heemink and Jacob van der Woude for making it possible to complete my graduation project at Rijkswaterstaat. My gratitude goes to everyone at Rijkswaterstaat who helped me improve my knowledge about fairways, the traffic on fairways and who were always open to discus my project. Without these people it would not have been possible to determine a model that comes this close to the situation observed in reality. Quirine de Kloet, December 2, 2016 Academic Supervisors: Prof.dr.ir. A.W. Heemink Dr. J.W. van der Woude Company Supervisor: Drs. K. Robaczewska Thesis committee: Prof.dr.ir. A.W. Heemink TU Delft, EEMCS (DIAM) Dr. J.W. van der Woude TU Delft, EEMCS (DIAM) Dr. M. Snelder TU Delft, CEG (Transport & Planning) Drs. K. Robaczewska Ministerie I&M, Rijkswaterstaat (CIV) Ir. L. Kuiters Ministerie I&M, Rijkswaterstaat (WVL) iii ABSTRACT There has been a lot of research done into traffic on roads and multiple traffic models have been set up for this type of traffic. A subject that has been largely neglected is the traffic on fairways. The research goal set for my graduation project is to define a model that can simulate the traffic on fairways and use this model to optimize the allocation of this traffic. To achieve this the existing traffic models have been investigated. This way a model was found that could be extended to fairway traffic, the mesoscopic model. Within the mesoscopic model there is a possibility to incorporate a more detailed microscopic model for the objects (locks and bridges). Several microscopic models were defined for the locks and bridges. Optimization models were set up based on previous work done into lock modeling. However, optimization models cannot include all rules used in reality; this makes heuristic models more efficient. For bridges the optimization model can be defined starting from the lock optimization. This optimization model can determine what the best time to open a bridge is. In the case of bridges the situation decides which model is best to use. When no information is available, the best result comes from an optimization model. Some bridges have fixed opening times; simply using this schedule gives the same result in less time. The mesoscopic model was implemented on a practical case in Zeeland. Using this model it is possible to gain insight into several elements: • Give a value to the efficient use of objects when traffic is spread over the day and night equally. • Effect of different situations that can occur when maintenance reduces the capacity of the network. • Effect of stimulating skippers to travel at a time when there is less traffic, optimizing the allocation of traffic. v CONTENTS Preface iii Abstract v List of Figures xi List of Tables xiii I Introduction 1 1 Introduction 3 1.1 Motivation of the project.....................................3 1.2 Research objective........................................4 1.3 Structure.............................................4 2 Previous work 5 2.1 Traffic models...........................................5 2.1.1 Microscopic models....................................5 2.1.2 Macroscopic models....................................5 2.1.3 Mesoscopic model for road traffic.............................5 2.1.4 Railway traffic.......................................6 2.2 Lock scheduling process.....................................6 2.2.1 Double optimization....................................6 2.3 SIVAK...............................................7 2.4 IVS90...............................................7 2.5 VCM Traffic-planner.......................................7 2.5.1 Lock scheduling method..................................7 2.5.2 Estimating traffic......................................7 2.5.3 Travel times........................................8 2.6 Usability in this project......................................8 2.6.1 Traffic models.......................................8 2.6.2 Lock scheduling process..................................8 2.6.3 VCM traffic-planner....................................8 2.6.4 Research objective.....................................9 II Model design 11 3 Modeling aspects 13 3.1 Fairway modeling......................................... 13 3.2 Ship information......................................... 14 3.3 Mesoscopic model........................................ 14 3.3.1 Extending the mesoscopic model to fairway traffic..................... 15 4 Object modeling 17 4.1 Different kinds of objects..................................... 17 4.1.1 Locks............................................ 17 4.1.2 Bridges........................................... 18 4.2 Lock model............................................ 18 4.2.1 Optimization model.................................... 19 4.2.2 Double optimization model................................ 20 4.2.3 Heuristic model - Rules.................................. 20 4.2.4 Placement heuristic.................................... 22 vii viii CONTENTS 4.2.5 Dangerous cargo...................................... 24 4.2.6 Comparison of the models................................. 25 4.2.7 Checks added for additional elements........................... 26 4.3 Bridge model........................................... 27 4.3.1 Optimization model.................................... 27 4.3.2 Schedule model...................................... 27 4.3.3 Comparison of the models................................. 28 5 Routing 29 5.1 Costs at nodes........................................... 29 5.2 Time dependent routing..................................... 30 5.3 Rerouting............................................. 30 5.4 Routing based on reliability.................................... 31 6 Simulation 33 6.1 Step 1: Pre-processing...................................... 33 6.2 Step 2: Simulation......................................... 34 6.2.1 Short edges........................................ 36 6.3 Step 3: Analysis.......................................... 38 6.4 Step 4: Changing routes or departure time............................ 38 6.5 What information to use and to save............................... 39 III Practical case 41 7 Practical case - Zeeland 43 7.1 Locks............................................... 44 7.1.1 Sub-chambers in locks................................... 45 7.2 Bridges.............................................. 45 7.3 Expected arrival time....................................... 46 IV Results 49 8 Basis simulation 51 8.1 Sub-chambers.......................................... 51 8.2 Bridges at locks.......................................... 52 8.3 Dangerous cargo......................................... 53 8.4 Increasing the amount of ships.................................. 53 8.4.1 Capacity usage....................................... 55 9 Maintenance at Kreekrak 57 9.1 Chamber closed completely................................... 57 9.2 Short maintenance........................................ 59 9.3 Different maintenance options.................................. 63 10 Optimizing the allocation of ships 65 10.1 Basis situation.......................................... 65 10.2 Increased amount of ships.................................... 66 10.3 Maintenance at Kreekrak..................................... 67 10.4 Increasing delays......................................... 67 11 Conclusion 69 11.1 Capacity usage of locks...................................... 69 11.2 Kreekrak............................................. 70 11.2.1 Chamber closed the whole day............................... 70 11.2.2 Short maintenance....................................