Contents Modeling Transportation Systems: Preliminary Concepts and Application Areas Transportation Supply Models

Transcription

1 1 Modeling Transportation Systems: Preliminary Concepts and Application Areas Introduction TransportationSystems TransportationSystemIdentification RelevantSpatialDimensions RelevantTemporalDimensions Relevant Components of Travel Demand ModelingTransportationSystems Model Applications and Transportation Systems Engineering Transportation Systems Design and the Decision-Making Process SomeAreasofApplication Reference Notes Transportation Supply Models Introduction Fundamentals of Traffic Flow Theory UninterruptedFlows Fundamental Variables Model Formulation Queuing Models Fundamental Variables Deterministic Models Stochastic Models Congested Network Models NetworkStructure Flows Performance Variables and Transportation Costs Link Performance and Cost Functions Impacts and Impact Functions General Formulation Applications of Transportation Supply Models Supply Models for Continuous Service Transportation Systems Graph Models Link Performance and Cost Functions Supply Models for Scheduled Service Transportation Systems Line-based Graph Models Link Performance and Cost Functions Reference Notes xi

2 xii 3 Random Utility Theory Introduction BasicAssumptions Some Random Utility Models The Multinomial Logit Model The Single-Level Hierarchical Logit Model The Multilevel Hierarchical Logit Model * The Cross-nested Logit Model * The Generalized Extreme Value (GEV) Model * The Probit Model The Mixed Logit Model * Expected Maximum Perceived Utility and Mathematical Properties of Random Utility Models ChoiceSetModeling Direct and Cross-elasticities of Random Utility Models Aggregation Methods for Random Utility Models A Derivation of Logit Models from the GEV Model A.1 Derivation of the Multinomial Logit Model A.2 Derivation of the Single-Level Hierarchical Logit Model A.3 Derivation of the Multilevel Hierarchical Logit Model A.4 Derivation of the Cross-nested Logit Model B Random Variables Relevant for Random Utility Models B.1 The Gumbel Random Variable B.2 The Multivariate Normal Random Variable Reference Notes Travel-Demand Models Introduction Trip-based Demand Model Systems Random Utility Models for Trip Demand Examples of Trip-based Demand Models Models of Spatial and Temporal Characteristics Trip Production or Trip Frequency Models Distribution Models Mode Choice Models Path Choice Models Path Choice Models for Road Networks Path Choice Models for Transit Systems A System of Demand Models Trip-Chaining Demand Models Activity-Based Demand Models A Theoretical Reference Framework Weekly Household Activity Model Daily Household Activity Model Daily Individual Activity List Model Activity Pattern and Trip-Chain Models...234

3 xiii 4.6 Applications of Demand Models Freight Transportation Demand Models Multiregional Input Output (MRIO) models Freight Mode Choice Models Reference Notes Basic Static Assignment to Transportation Networks Introduction Classification of Assignment Models Fields of Application of Assignment Models Definitions,Assumptions,andBasicEquations Supply Model Demand Model Feasible Path and Link Flow Sets Network Performance Indicators Uncongested Networks Models for Stochastic Assignment Models for Deterministic Assignment Algorithms Without Explicit Path Enumeration Congested Networks: Equilibrium Assignment Models for Stochastic User Equilibrium Algorithms for Stochastic User Equilibrium Models for Deterministic User Equilibrium Algorithms for Deterministic User Equilibrium Relationship Between Stochastic and Deterministic Equilibrium System Optimum Assignment * ResultInterpretationandParameterCalibration Specification and Calibration of Assignment Models A Optimization Models for Stochastic Assignment A.1 Uncongested Network: Stochastic Assignment A.2 Congested Network: Stochastic User Equilibrium Reference Notes Assignment Models AssignmentAlgorithms Advanced Models for Traffic Assignment to Transportation Networks Introduction AssignmentwithPre-trip/En-routePathChoice Definitions,Assumptions,andBasicEquations Uncongested Networks Congested Networks: Equilibrium Assignment Equilibrium Assignment with Variable Demand Single-ModeAssignment...368

4 xiv Models for Stochastic User Equilibrium Models for Deterministic User Equilibrium Algorithms Multimode Equilibrium Assignment Multiclass Assignment Undifferentiated Congestion Multiclass Assignment Differentiated Congestion Multiclass Assignment Interperiod Dynamic Process Assignment Definitions,Assumptions,andBasicEquations Supply Model Demand Model Approaches to Dynamic Process Modeling Deterministic Process Models Stochastic Process Models Synthesis and Application Issues Reference Notes Intraperiod (Within-Day) Dynamic Models * Introduction Supply Models for Transport Systems with Continuous Service Space-Discrete Macroscopic Models VariablesandConsistencyConditions Network Flow Propagation Model Link Performance and Travel Time Functions Dynamic Network Loading Path Performance and Travel Time Functions Formalization of the Whole Supply Model Mesoscopic Models VariablesandConsistencyConditions Link Performance and Travel Time Functions Path Performance and Travel Time Functions Dynamic Network Loading Formalization of the Whole Supply Model Demand Models for Continuous Service Systems Demand Supply Interaction Models for Continuous Service Systems Uncongested Network Assignment Models User Equilibrium Assignment Models Dynamic Process Assignment Models Dynamic Traffic Assignment with Nonseparable Link Cost Functions and Queue Spillovers Network Performance Model Exit Capacity Model Exit Flow and Travel Time Model Entry Capacity Model...475

5 xv Fixed-PointFormulationoftheNPM Network Loading Map and Fixed-Point Formulation of the Equilibrium Model Models for Transport Systems with Scheduled Services Models for Regular Low-Frequency Services Supply Models Demand Models Demand Supply Interaction Models Models for Irregular High-Frequency Services Supply Models Demand Models Demand Supply Interaction Models A The Simplified Theory of Kinematic Waves Based on Cumulative Flows: Application to Macroscopic Link Performance Models A.1 Bottlenecks A.2 Segments Reference Notes Estimation of Travel Demand Flows Introduction DirectEstimationofPresentDemand SamplingSurveys SamplingEstimators Disaggregate Estimation of Demand Models Model Specification Model Calibration Model Validation Disaggregate Estimation of Demand Models with Stated Preference Surveys * Definitions and Types of Survey SurveyDesign Model Calibration Estimation of O-D Demand Flows Using Traffic Counts Maximum Likelihood and GLS Estimators Bayesian Estimators ApplicationIssues Solution Methods Aggregate Calibration of Demand Models Using Traffic Counts Estimation of Within-Period Dynamic Demand Flows Using Traffic Counts Simultaneous Estimators Sequential Estimators Real-Time Estimation and Prediction of Within-Period Dynamic Demand Flows Using Traffic Counts Applications of Demand Estimation Methods

6 xvi EstimationofPresentDemand Estimation of Demand Variations (Forecasting) Reference Notes Transportation Supply Design Models Introduction General Formulations of the Supply Design Problem Applications of Supply Design Models Models for Road Network Layout Design Models for Road Network Capacity Design Models for Transit Network Design Models for Pricing Design Models for Mixed Design Some Algorithms for Supply Design Models AlgorithmsfortheDiscreteSDP Algorithms for the Continuous SDP Reference Notes Methods for the Evaluation and Comparison of Transportation System Projects Introduction EvaluationofTransportationSystemProjects Identification of Relevant Impacts Identification and Estimation of Impact Indicators Computation of Users Surplus Changes Methods for the Comparison of Alternative Projects Benefit-Cost Analysis Revenue-Cost Analysis Multi-criteria Analysis Noncompensatory Methods * Multiattribute Utility Theory Method (MAUT) * Linear Additive Methods * The Analytical Hierarchy Process (AHP) * Outranking Methods * Constrained Optimization Method * Reference Notes Appendix A Review of Numerical Analysis A.1 Sets and Functions A.1.1 Elements of Set Topology A.1.2 Continuous and Differentiable Functions A.1.3 Convex Functions A.2 SolutionAlgorithms A.3 Fixed-PointProblems A.3.1 Properties of Fixed-Points A.3.2 SolutionAlgorithmsforFixed-PointProblems...695

7 xvii A.4 OptimizationProblems A.4.1 Properties of Minimum Points A Properties of Minimum Points on Open Sets A Properties of Minimum Points on Closed Sets A.4.2 SolutionAlgorithmsforOptimizationProblems A Monodimensional Optimization Algorithms A Unconstrained Multidimensional Optimization Algorithms A Bounded Variables Multidimensional A OptimizationAlgorithms Linearly Constrained Multidimensional OptimizationAlgorithms A.5 Variational Inequality Problems A.5.1 Properties of Variational Inequalities A.5.2 Solution Algorithms for Variational Inequality Problems Index References...725

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