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MODELLING TRANSPORT
Comprehensive Textbook Resource for Understanding Transport Modelling
Modelling Transport provides unrivalled depth and breadth of coverage on the topic of transport modelling. 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. An accompanying website hosts a solutions manual.
Sample topics and learning resources included in the work are as follows:
Graduate students in transportation engineering and planning, transport economics, urban studies, and geography programs along with researchers and practitioners in the transportation and urban planning industry can use Modelling Transport as a comprehensive reference work for a wide array of topics pertaining to this field.
Auteur
Dr. Juan de Dios Ortúzar is Emeritus Professor in the School of Engineering at Pontificia Universidad Católica de Chile and also Key Researcher at Instituto Sistemas Complejos de Ingeniería (ISCI) and the BRT+ Centre of Excellence. He has over 30 years of experience in discrete choice modelling and survey design with particular focus on transport demand modelling and the valuation of transport externalities. Dr. Luis G. Willumsen is an internationally recognised authority in transport and traffic modelling and has over 30 years of experience in this area. He previously lectured at Leeds University and University College London, and was also a Director of Steer before leaving in 2009 to set up his own independent practice. He is also Managing Partner of Nommon Solutions and Technologies, a company processing big data to provide location and mobility intelligence.
Texte du rabat
Comprehensive Textbook Resource for Understanding Transport Modelling Modelling Transport provides unrivalled depth and breadth of coverage on the topic of transport modelling. 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. An accompanying website hosts a solutions manual. Sample topics and learning resources included in the work are as follows:
Contenu
Preface xviii
About the Companion Website xxii
1 Introduction 1
1.1 Background 1
1.2 Models and Their Role 2
1.3 Characteristics of Transport Problems 3
1.3.1 Characteristics of Transport Demand 3
1.3.2 Characteristics of Transport Supply 4
1.3.3 A View of Transport Problems 6
1.3.4 A Simple Model 7
1.3.5 Classic and New Modes of Transport 9
1.4 Modelling and Decision-Making 9
1.5 Issues in Transport Modelling 12
1.5.1 General Modelling Issues 12
1.5.1.1 The Roles of Theory and Data 12
1.5.1.2 Model Assumptions 13
1.5.1.3 Model Specification 14
1.5.1.4 Model Calibration, Validation, and Use 15
1.5.1.5 Modelling, Forecasting, and Judgement 16
1.5.2 Aggregate and Disaggregate Modelling 17
1.5.3 Homo Sapiens and Homo Economicus 18
1.5.4 Cross-Section and Time Series 20
1.5.5 Revealed and Stated Preferences 21
1.6 The Structure of the Classic Transport Model 22
1.6.1 The Classic 4/5 Stage Model 22
1.6.2 Granularity 24
1.6.3 Macro, Meso, and Micro Models 27
1.7 Transport Planning and Uncertainty 27
1.8 Theoretical Basis Versus Expedience 31
1.9 Becoming a Better Modeller 33
Exercises 33
2 Data 35
2.1 Basic Sampling Theory 36
2.1.1 Statistical Considerations 36
2.1.1.1 Basic Definitions 36
2.1.1.2 Sample Size to Estimate Population Parameters 38
2.1.1.3 Obtaining the Sample 40
2.1.2 Practical Considerations in Sampling 43
2.1.2.1 The Implementation Problem 43
2.1.2.2 Finding the Size of Each Subpopulation 43
2.2 Errors in Modelling and Forecasting 44
2.2.1 Different Types of Error 45
2.2.1.1 Measurement Errors 45
2.2.1.2 Sampling Errors 46
2.2.1.3 Computational Errors 46
2.2.1.4 Specification Errors 46
2.2.1.5 Transfer Errors 47
2.2.1.6 Aggregation Errors 47
2.2.2 The Model Complexity/Data Accuracy Trade-off 48
2.2.3 Forecasting Errors 51
2.3 Basic Data-collection Methods 53
2.3.1 Practical Considerations 53
2.3.1.1 Length of the Study 53
2.3.1.2 Study Horizon 53
2.3.1.3 Limits of the Study Area 54
2.3.1.4 Study Resources 54
2.3.2 Types of Surveys 54
2.3.2.1 Survey Scope 55
2.3.2.2 Home Interview Travel Surveys 57
2.3.2.3 Other Important Types of Surveys 66
2.3.3 Data Correction, Expansion, and Validation 68
2.3.3.1 Data Correction 69
2.3.3.2 Imputation Methods 71
2.3.3.3 Sample Expansion 72
2.3.3.4 Validation of Results 72
2.3.4 Longitudinal Data Collection 73
2.3.4.1 Basic Definitions 73
2.3.4.2 Representative Sampling 74
2.3.4.3 Sources of Error in Panel Data 75
2.3.4.4 Relative Costs of Longitudinal Surveys 76
2.3.5 Travel Time Surveys 76
2.3.6 Digital Data Sources 77
2.4 Stated Preference Surveys 79
2.4.1 Introduction 79
2.4.1.1 Contingent Valuation and Conjoint Analysis 79
2.4.1.2 Stated Choice Methods 81
2.4.2 The Survey Process 83
2.4.2.1 Clarifying Study Objectives and Defining Objects of Interest 84
2.4.2.2 Defining Experimental Assumptions 86
2.4.2.3 Generating the Experimental Design 92
2.4.2.4 Conduct Post Design Generation Testing 97
2.4.2.5 Conduct Questionnaire 98
2.4.2.6 Nothing is Important 99
2.4.2.7 Realism and Complexity 100
2.4.2.8 Use of Computers in SP Surveys 101
2.4.2.9 Quality Issues in Stated Preference Surveys 102
2.4.3 Case Study Example 103
2.4.4 Limitations of Stated Preference Methods 115
Exercises 115
3 Zones and Networks 119
3.1 Zoning Design 120
3.2 Road Network Representation 122
3.2.1 Traffic Flow 123
3.2.2 Network Details 123
3.3 Link Properties and Functions 125
3.3.1 Link Properties 125
3.3.2 Network Costs 126
3.3.3 Definitions and Notation 127
3.3.4 Speed-Flow and Cost-Flow Curves 127
3.3.5 Public Transport Networks 131
Exercises 132
4 Trip Generation Modelling 133
4.1 Introduction 134
4.1.1 Some Basic Definitions 134
4.1.2 Characterisation of Journeys 135
4.1.2.1 By Purpose 135
4.1.2.2 By Time of Day 135
4.1.2.3 By Person Type 136
4.1.3 Factors Affecting Trip Generation 136
4.1.3.1 Personal Trip Productions 137
4.1.3.2 Personal Trip Attractions 137
4.1.3.3 Freight Trip Productions and Attractions 137
4.1.4 Growth-Factor Modelling 138
4.2 Regression Analysis 139
4.2.1 The Linear Regression Model 139
4.2.2 Zonal-Based Multiple Regression…