| Preface | 5 |
|---|
| Table of Contents | 9 |
|---|
| Scientific Board | 11 |
|---|
| List of Contributors | 12 |
|---|
| Fifty Years of Urban Modeling: Macro-Statics to Micro-Dynamics | 19 |
|---|
| 1 Historical Antecedents | 19 |
| 2 The Time-Lines: Cities, Planning, Modeling | 22 |
| 3 Deconstructing the Urban Modeling Time-Line | 26 |
| 4 The Quest for Dynamics: The Macro Perspective | 31 |
| 5 Towards Micro Dynamics: Agents, Cells and the New Social Physics | 33 |
| 6 What Has Been Achieved: Retrospect and Prospect | 35 |
| References | 36 |
| Complexity: the Integrating Framework for Models of Urban and Regional Systems | 39 |
|---|
| 1 Introduction | 39 |
| 2 Evolutionary Complex Systems | 40 |
| 3 Dynamic, Spatial Urban Models | 46 |
| 4 Manufacturing Evolution | 50 |
| 5 Structural Attractors | 55 |
| 6 Conclusions | 57 |
| References | 58 |
| Ontogeny and Ontology in Complex Systems Modeling | 60 |
|---|
| 1 Introduction | 60 |
| 2 Dynamical Hierarchies | 61 |
| 3 Ontogeny | 63 |
| 4 The Network Model | 66 |
| 5 Discussion | 70 |
| References | 74 |
| A Model for Asystematic Mobility in Urban Space | 76 |
|---|
| 1 Introduction | 76 |
| 2 The Mobilis in Mobile Model | 77 |
| 3 Applications to Realistic Situations and Experiments | 85 |
| 4 Conclusions | 89 |
| Acknowledgments | 89 |
| References | 89 |
| Preliminary Results of a Multi-Agent Traffic Simulation for Berlin | 91 |
|---|
| 1 Introduction | 91 |
| 2 The Model | 92 |
| 3 Set-Up of the Berlin Simulations | 98 |
| 4 Preliminary Results | 103 |
| 5 Discussion | 106 |
| 6 Summary and Conclusion | 107 |
| References | 107 |
| Hybrid Geographical Models of Urban Spatial Structure and Behaviour | 111 |
|---|
| 1 Introduction | 111 |
| 2 Microsimulation and Spatial Evolution | 112 |
| 3 Simple Models of the Urban Labour Market | 114 |
| 4 Semi-Aggregate Models of the Urban Labour Market | 118 |
| 5 An Interacting Fields Model | 120 |
| 6 Conclusions | 123 |
| References | 124 |
| Two Complexities and a Few Models | 126 |
|---|
| 1 Premises | 126 |
| 2 What Is a Good Model? | 131 |
| 3 Why Planning Is (Still) a Necessity and Why It Needs Models | 132 |
| 4 A Tool-Box for Planning | 134 |
| 5 The Time Machine | 144 |
| Conclusions | 153 |
| References | 154 |
| Cities as Evolutionary Systems in Random Media1 | 157 |
|---|
| 1 Introduction | 157 |
| 2 The Model | 160 |
| 3 First-Order Quenched Moment | 162 |
| 4 The Feynman–Kac Formula | 163 |
| 5 Lyapunov Exponents for | 164 |
| 6 Intermittency of | 167 |
| 7 Higher-Order Quenched Moments | 169 |
| 8 Adequacy of Moments | 171 |
| 9 Concluding Remarks | 172 |
| Acknowledgements | 173 |
| References | 174 |
| Grilling the Grid: a Non-Ultimate (Nor Objective) Report on the Configurational Approach to Urban Phenomena | 176 |
|---|
| 1 Introduction | 176 |
| 2 The Configurational Approach: Conceptual Basis | 178 |
| 3 The Configurational Approach: Techniques and Methods | 182 |
| 4 Operational Techniques: the | 182 |
| 5 Operational Techniques: the | 189 |
| 6 Operational Techniques: Potentials, Limits and Integrations | 191 |
| 6 Conclusions | 194 |
| References | 195 |
| Validating and Calibrating Integrated Cellular Automata Based Models of Land Use Change | 197 |
|---|
| 1 Introduction | 197 |
| 2 The Validation Problem | 199 |
| 3 A Case Study of Calibration: ENVIRONMENT Explorer | 207 |
| 4 Semi-Automatic Calibration and Validation of Environment Explorer | 211 |
| 5 Results - The Pilot Case: ENVIRONMENT Explorer for the Netherlands | 218 |
| 6 Discussion | 220 |
| 7 Conclusions | 221 |
| References | 222 |
| Fractal Geometry for Measuring and Modelling Urban Patterns | 224 |
|---|
| 1 Some Features of Urban Patterns | 224 |
| 2 Fractal Models for Urban Patterns | 229 |
| 3 Measuring Fractal Behaviour of Urban Patterns | 234 |
| 4 Some Empirical Results | 240 |
| 5 Urban Pattern Morphogenesis as Self-Organisation Process | 245 |
| 5 Conceptual Conclusions | 249 |
| Acknowledgments | 252 |
| References | 252 |
| Cartographic Data Sources for Figures | 254 |
| The Dynamics of Complex Urban Systems: Theory and Application of the STASA-Model within the Scatter Project | 255 |
|---|
| 1 Introduction | 255 |
| 2 The Stuttgart Case City | 256 |
| 3 The STASA Land-Use and Transport Modelling Framework | 258 |
| 4 Results of the Simulated Scenarios | 265 |
| References | 273 |
| Study of Urban Developers’ Behavior in a Game Environment | 275 |
|---|
| 1 Introduction | 275 |
| 2 From “Memory” to “Delay:” Markov Process as a Landmark | 276 |
| 3 Description of the Experiment | 279 |
| 4 Analysis of the Experiment | 282 |
| 5 From Transition Rules to Integral Description of Participants' Behavior | 287 |
| 6 The Simulation Model of Participants' Behavior | 288 |
| 8 Evaluation of Model Results | 290 |
| 9 Behavior of the Human Participant Versus the Model | 293 |
| Acknowledgements | 294 |
| References | 295 |
| Self-Organization and Optimization of Pedestrian and Vehicle Traffic in Urban Environments | 297 |
|---|
| 1 Spatio-Temporal Patterns in Pedestrian Flows | 297 |
| 2 Trail Formation | 307 |
| 3 Self-Organized Traffic Light Control | 311 |
| 4 Summary and Conclusions | 316 |
| Acknowledgments | 317 |
| References | 317 |
| Multidimensional Events in Multilevel Systems | 320 |
|---|
| 1 Introduction | 320 |
| 2 Relations and Structure: Graphs and Networks Are Not Rich Enough | 321 |
| 2 Simplicial Complexes and Emergence | 323 |
| 3 Hierarchical Aggregation | 324 |
| 4 Alpha- and Beta-Aggregations in Lattices Hierarchies | 325 |
| 5 What Is a City? | 326 |
| 6 Multidimensional Connectivity and Q-Analysis | 330 |
| 7 Backcloth and Traffic in Multilevel Systems | 332 |
| 8 Polyhedral Events and Order-2 Dynamics | 333 |
| 9 Examples | 336 |
| 10 Conclusions | 342 |
| Acknowledgement | 343 |
| Reference
|