Already the market leader in the field, Modelling Transport has become still more indispensible following a thorough and detailed update. Enhancements include two entirely new chapters on modelling for private sector projects and on activity-based modelling; a new section on dynamic assignment and micro-simulation; and sizeable updates to sections on disaggregate modelling and stated preference design and analysis. It also tackles topical issues such as valuation of externalities and the role of GPS in travel time surveys.Providing unrivalled depth and breadth of coverage, each topic is approached as a modelling exercise with discussion of the roles of theory, data, model specification, estimation, validation and application. The authors present the state of the art and its practical application in a pedagogic manner, easily understandable to both students and practitioners.Follows on from the highly successful third edition universally acknowledged as the leading text on transport modelling techniques and applicationsIncludes two new chapters on modelling for private sector projects and activity based modeling, and numerous updates to existing chaptersIncorporates treatment of recent issues and concerns like risk analysis and the dynamic interaction between land use and transportProvides comprehensive and rigorous information and guidance, enabling readers to make practical use of every available techniqueRelates the topics to new external factors and technologies such as global warming, valuation of externalities and global positioning systems (GPS).
Author(s): Juan de Dios Ortúzar, Luis G. Willumsen
Edition: 4th
Publisher: Wiley
Year: 2011
Language: English
Pages: 608
Tags: Транспорт;Технология и организация перевозок;
MODELLING
TRANSPORT......Page 3
Contents......Page 7
About the Authors......Page 17
Preface......Page 19
1.1.1 Background......Page 23
1.1.2 Models and their Role......Page 24
1.2.1 Characteristics of Transport Demand......Page 25
1.2.2 Characteristics of Transport Supply......Page 26
1.2.3 Equilibration of Supply and Demand......Page 28
1.3.1 Decision-making Styles......Page 30
1.3.2 Choosing Modelling Approaches......Page 32
1.4.1 General Modelling Issues......Page 36
1.4.2 Aggregate and Disaggregate Modelling......Page 40
1.4.3 Cross-section and Time Series......Page 41
1.5 The Structure of the Classic Transport Model......Page 42
1.6 Continuous Transport Planning......Page 45
1.7 Theoretical Basis Versus Expedience......Page 48
2.1 Introduction......Page 51
2.2.1 Introduction......Page 52
2.2.2 Functions and Graphs......Page 53
2.2.3 Sums of Series......Page 56
2.3.1 Introduction......Page 57
2.3.2 Basic Operations of Matrix Algebra......Page 58
2.4.1 Differentiation......Page 59
2.4.2 Integration......Page 60
2.4.3 The Logarithmic and Exponential Functions......Page 61
2.4.4 Finding Maximum and Minimum Values of Functions......Page 62
2.4.5 Functions of More Than One Variable......Page 63
2.4.7 Elasticities......Page 65
2.5.1 Probabilities......Page 66
2.5.2 Random Variables......Page 68
2.5.3 Moments around Zero......Page 69
2.5.4 More Advanced Statistical Concepts......Page 70
3.1.1 Statistical Considerations......Page 77
3.1.2 Conceptualisation of the Sampling Problem......Page 82
3.1.3 Practical Considerations in Sampling......Page 85
3.2.1 Different Types of Error......Page 87
3.2.2 The Model Complexity/Data Accuracy Trade-off......Page 90
3.3.1 Practical Considerations......Page 93
3.3.2 Types of Surveys......Page 95
3.3.3 Survey Data Correction, Expansion and Validation......Page 108
3.3.4 Longitudinal Data Collection......Page 112
3.3.5 Travel Time Surveys......Page 115
3.4.1 Introduction......Page 116
3.4.2 The Survey Process......Page 121
3.4.3 Case Study Example......Page 139
3.5 Network and Zoning Systems......Page 150
3.5.1 Zoning Design......Page 151
3.5.2 Network Representation......Page 153
Exercises......Page 157
4.1.1 Some Basic Definitions......Page 161
4.1.2 Characterisation of Journeys......Page 163
4.1.3 Factors Affecting Trip Generation......Page 164
4.1.4 Growth-factor Modelling......Page 165
4.2.1 The Linear Regression Model......Page 166
4.2.2 Zonal-based Multiple Regression......Page 173
4.2.3 Household-based Regression......Page 175
4.2.4 The Problem of Non-Linearity......Page 176
4.2.6 Matching Generations and Attractions......Page 178
4.3.1 The Classical Model......Page 179
4.3.2 Improvements to the Basic Model......Page 181
4.3.3 The Person-category Approach......Page 184
4.4 Trip Generation and Accessibility......Page 186
4.5 The Frequency Choice Logit Model......Page 187
4.6 Forecasting Variables in Trip Generation Analysis......Page 189
4.7.1 Temporal Stability......Page 190
4.7.2 Geographic Stability......Page 191
4.7.3 Bayesian Updating of Trip Generation Parameters......Page 192
Exercises......Page 194
5 Trip Distribution Modelling......Page 197
5.1 Definitions and Notation......Page 198
5.2.1 Uniform Growth Factor......Page 200
5.2.2 Singly Constrained Growth-Factor Methods......Page 201
5.2.3 Doubly Constrained Growth Factors......Page 202
5.2.4 Advantages and Limitations of Growth-Factor Methods......Page 203
5.3.1 The Gravity Distribution Model......Page 204
5.3.2 Singly and Doubly Constrained Models......Page 205
5.4.1 Entropy and Model Generation......Page 206
5.4.2 Generation of the Gravity Model......Page 208
5.4.3 Properties of the Gravity Model......Page 210
5.4.4 Production/Attraction Format......Page 212
5.5.1 Calibration and Validation......Page 213
5.5.2 Calibration Techniques......Page 214
5.6.1 Bi-proportional Fitting......Page 215
5.6.2 A Tri-proportional Problem......Page 217
5.6.3 Partial Matrix Techniques......Page 218
5.7.1 Generalisations of the Gravity Model......Page 220
5.7.2 Intervening Opportunities Model......Page 221
5.7.3 Disaggregate Approaches......Page 222
5.8.3 Intra-zonal Trips......Page 223
5.8.6 Errors in Modelling......Page 224
5.8.7 The Stability of Trip Matrices......Page 226
Exercises......Page 227
6.1 Introduction......Page 229
6.2 Factors Influencing the Choice of Mode......Page 230
6.4 Trip Interchange Heuristics Modal-split Models......Page 231
6.5.1 Distribution and Modal-split Models......Page 233
6.5.2 Distribution and Modal-split Structures......Page 235
6.5.3 Multimodal-split Models......Page 236
6.5.4 Calibration of Binary Logit Models......Page 239
6.5.5 Calibration of Hierarchical Modal-split Models......Page 240
6.6.1 Introduction......Page 241
6.6.2 Direct Demand Models......Page 242
6.6.3 An Update on Direct Demand Modelling......Page 243
Exercises......Page 245
7.1 General Considerations......Page 249
7.2 Theoretical Framework......Page 252
7.3.1 Specification Searches......Page 254
7.3.2 Universal Choice Set Specification......Page 255
7.3.3 Some Properties of the MNL......Page 256
7.4.1 Correlation and Model Structure......Page 257
7.4.2 Fundamentals of Nested Logit Modelling......Page 259
7.4.3 The NL in Practice......Page 262
7.4.4 Controversies about some Properties of the NL Model......Page 263
7.5.1 The Binary Probit Model......Page 270
7.5.2 Multinomial Probit and Taste Variations......Page 271
7.6.1 Model Formulation......Page 272
7.6.2 Model Specifications......Page 273
7.6.3 Identification Problems......Page 276
7.7.2 Choice by Elimination and Satisfaction......Page 278
7.7.3 Habit and Hysteresis......Page 280
7.7.4 Modelling with Panel Data......Page 281
7.7.5 Hybrid Choice Models Incorporating Latent Variables......Page 287
Exercises......Page 288
8.1 Introduction......Page 291
8.2.1 Choice-set Size......Page 292
8.2.2 Choice-set Formation......Page 293
8.3.1 Functional Form and Transformations......Page 294
8.3.2 Theoretical Considerations and Functional Form......Page 295
8.3.3 Intrinsic Non-linearities: Destination Choice......Page 296
8.4.1 Estimation of Models from Random Samples......Page 297
8.4.3 Estimation of Hybrid Choice Models with Latent Variables......Page 310
8.4.4 Comparison of Non-nested Models......Page 313
8.5.1 Numerical Integration......Page 314
8.5.2 Simulated Maximum Likelihood......Page 315
8.5.3 Advanced Techniques......Page 316
8.6 Estimating the Mixed Logit Model......Page 317
8.6.1 Classical Estimation......Page 318
8.6.2 Bayesian Estimation......Page 320
8.6.3 Choice of a Mixing Distribution......Page 324
8.6.4 Random and Quasi Random Numbers......Page 327
8.6.5 Estimation of Panel Data Models......Page 329
8.7 Modelling with Stated-Preference Data......Page 330
8.7.1 Identifying Functional Form......Page 331
8.7.2 Stated Preference Data and Discrete Choice Modelling......Page 332
8.7.3 Model Estimation with Mixed SC and RP Data......Page 344
Exercises......Page 351
9.1 Introduction......Page 355
9.2 Aggregation Bias and Forecasting......Page 356
9.3 Confidence Intervals for Predictions......Page 357
9.3.1 Linear Approximation......Page 358
9.3.2 Non Linear Programming......Page 359
9.4 Aggregation Methods......Page 360
9.5.2 Methods to Evaluate Model Transferability......Page 363
9.5.3 Updating with Disaggregate Data......Page 365
9.5.4 Updating with Aggregate Data......Page 366
Exercises......Page 367
10.1.1 Introduction......Page 371
10.1.2 Definitions and Notation......Page 372
10.1.3 Speed–Flow and Cost–Flow Curves......Page 373
10.2.1 Introduction......Page 377
10.2.2 Route Choice......Page 378
10.2.3 Tree Building......Page 380
10.3 All-or-nothing Assignment......Page 381
10.4.1 Simulation-Based Methods......Page 383
10.4.2 Proportional Stochastic Methods......Page 384
10.4.3 Emerging Approaches......Page 386
10.5.1 Wardrop’s equilibrium......Page 389
10.5.3 Incremental Assignment......Page 391
10.5.4 Method of Successive Averages......Page 392
10.5.5 Braess’s Paradox......Page 394
10.6.2 Issues in Public-Transport Assignment......Page 395
10.6.3 Modelling Public-Transport Route Choice......Page 398
10.6.4 Assignment of Transit Trips......Page 402
10.7.1 Limitations in the Node-link Model of the Road Network......Page 403
10.7.5 Day-to-day Variations in Demand......Page 404
10.7.7 The Dynamic Nature of Traffic......Page 405
10.7.8 Input Errors......Page 406
10.8 Practical Considerations......Page 407
Exercises......Page 410
11.1 Introduction......Page 413
11.2.1 A Mathematical Programming Approach......Page 414
11.2.2 Social Equilibrium......Page 418
11.2.3 Solution Methods......Page 419
11.2.4 Stochastic Equilibrium Assignment......Page 423
11.2.5 Congested Public Transport Assignment......Page 425
11.3.1 Equilibrium and Feedback......Page 426
11.3.2 Formulation of the Combined Model System......Page 428
11.3.3 Solving General Combined Models......Page 431
11.3.4 Monitoring Convergence......Page 432
11.4.1 The Dynamic Nature of Traffic......Page 433
11.4.2 Travel Time Reliability......Page 435
11.4.3 Junction Interaction Methods......Page 436
11.4.4 Dynamic Traffic Assignment (DTA)......Page 437
11.5.1 Introduction......Page 442
11.5.3 Underlying Principles of Micro Departure Time Choice......Page 443
11.5.4 Simple Supply/Demand Equilibrium Models......Page 445
11.5.5 Time of Travel Choice and Equilibrium Assignment......Page 446
11.5.6 Conclusion......Page 447
Exercises......Page 448
12.1 Introduction......Page 451
12.2 Sketch Planning Methods......Page 452
12.3.1 Incremental Elasticity Analysis......Page 453
12.3.2 Incremental or Pivot-point Modelling......Page 455
12.4.1 Introduction......Page 457
12.4.3 Transport Model Estimation from Traffic Counts......Page 458
12.4.4 Matrix Estimation from Traffic Counts......Page 461
12.4.5 Traffic Counts and Matrix Estimation......Page 466
12.4.6 Limitations of ME2......Page 468
12.4.7 Improved Matrix Estimation Models......Page 469
12.4.8 Treatment of Non-proportional Assignment......Page 470
12.4.10 Estimation of Trip Matrix and Mode Choice......Page 472
12.5.1 Introduction......Page 474
12.5.2 Corridor Models......Page 475
12.5.3 Marginal Demand Models......Page 476
12.6 Gaming Simulation......Page 478
Exercises......Page 480
13.1 Importance......Page 483
13.2 Factors Affecting Goods Movements......Page 484
13.4 Data Collection for Freight Studies......Page 485
13.5.2 Distribution Models......Page 488
13.5.4 Assignment......Page 490
13.5.5 Equilibrium......Page 491
13.6 Disaggregate Approaches......Page 492
13.7 Some Practical Issues......Page 493
14.1 Introduction......Page 495
14.2 Activities, Tours and Trips......Page 496
14.3 Tours, Individuals and Representative Individuals......Page 499
14.4 The ABM System......Page 500
14.5 Population Synthesis......Page 501
14.6 Monte Carlo and Probabilistic Processes......Page 503
14.7 Structuring Activities and Tours......Page 504
14.8 Solving ABM......Page 506
14.9 Refining Activity or Tour Based Models......Page 507
14.10 Extending Random Utility Approaches......Page 509
15.1.1 Introduction......Page 511
15.1.2 Use of Official Forecasts......Page 512
15.1.3 Forecasting Population and Employment......Page 513
15.2 Land-Use Transport Interaction Modelling......Page 515
15.2.1 The Lowry Model......Page 517
15.2.2 The Bid-Choice Model......Page 518
15.2.3 Systems Dynamics Approach......Page 519
15.3.1 Background......Page 521
15.3.2 Time-series Extrapolations......Page 522
15.3.3 Econometric Methods......Page 525
15.3.4 International Comparisons......Page 529
15.4.2 Subjective and Social Values of Time......Page 531
15.4.3 Some Practical Results......Page 532
15.4.4 Methods of Analysis......Page 534
15.5.1 Introduction......Page 544
15.5.2 Methods of Analysis......Page 546
Exercises......Page 552
16.1.1 Background......Page 555
16.1.3 Modelling and Forecasting......Page 556
16.2.1 Involvement of Private Sector in Transport Projects......Page 557
16.2.2 Agents and Processes......Page 558
16.3.1 Uncertainty and Risk......Page 560
16.4.1 Willingness to Pay......Page 561
16.4.2 Simple Projects......Page 562
16.4.3 Complex Projects......Page 563
16.4.4 Project Preparation......Page 564
16.4.6 Ramp Up, Expansion, Leakage......Page 566
16.5 Risk Analysis......Page 567
16.5.1 Sensitivity and Sources of Risk......Page 568
16.5.2 Stochastic Risk Analysis......Page 569
16.6 Concluding Remarks......Page 570
References......Page 573
Index......Page 603
