C O N T E N T S 1 Chapter 1 Summary 1.1 Need for Solid Traffic and Revenue (T&R) Forecasts 1 1.2 State of the Practice and Challenges in T&R Forecasting 1 1.2.1 Main Factors Affecting Reasonability of T&R Forecast 2 1.2.2 State of the Practice and Major Gaps Identified 2 1.2.3 Recommended Short-Term Improvements 3 1.2.4 Recommended Long-Term Improvements and Strategic Directions 3 1.3 Model Features Required for Different Pricing Studies 4 1.3.1 Model Features for Different Pricing Projects 5 1.3.2 Model Features for Different Stages of Decision Making 5 1.3.3 Specific Requirements for Forecasting Tools for Investment 8 Grade Studies 1.4 Organization of Volume 2 10 Chapter 2 State of the Practice in Forecasting Methods 11 2.1 Basics of T&R Forecasting 11 2.2 Travel Cost Representation in Demand and Network Models 12 2.3 Models Included in the Synthesis 15 2.4 Conclusions from the Review of Existing Models 15 Chapter 3 Survey Methods to Support Pricing Studies 20 3.1 Overview of Survey Methods to Support Pricing Studies 20 3.2 Summary and Proposed Practice Guidelines 22 Chapter 4 Critical Issues and Directions for Short-Term Improvements 24 4.1 Classification of Model Features Required for Pricing Studies 24 4.1.1 Model Features for Different Pricing Projects 24 4.1.2 Model Features for Different Stages of Decision Making 26 4.1.3 Specific Requirements for Forecasting Tools for Investment Grade Studies 29 4.2 Prototype Structure of Travel Model for Pricing Studies 33 4.2.1 Main Travel Dimensions Affected by Pricing 33 4.2.2 Observed Impacts of Pricing on Different Travel Choices (PSRC Experiment) 34 4.2.3 Prototype Structure of Demand Model-4-Step Approach 39 4.2.4 Prototype Structure of Demand Model-Activity-Based Approach 40 4.2.5 Prototype Structure of Network Assignments 41 4.3 Summary of Key Model Parameters 44 4.3.1 VOT Values in Applied Models 44 4.3.2 Recommended Values for VOT, Travel Time, and Cost Coefficients 52 4.4 Model Validation, Calibration, and Sensitivity Testing 54 4.4.1 Dimensions and Data for Model Validation 54 4.4.2 Region-Level Calibration Procedures 55 4.4.3 Corridor-Level and Sub-Area-Level Calibration Procedures 57 4.4.4 Sensitivity Tests, Risk Analysis, and Mitigation 58 4.5 Adjustment of Travel Cost Inputs and Coefficients for Future Years 65 4.5.1 Model Input and Coefficient Consistency for Different Years 65 4.5.2 Reasons for Adjustment 65 4.5.3 Approaches and Time Horizons for Adjustment 66 4.5.4 Adjustment Strategies for Different Types of Cost Variables 66 4.6 Evaluation of Pricing Projects 67 4.6.1 Benefit and Cost Calculation 68 4.6.2 Criteria for Evaluation of Pricing Projects 71 Chapter 5 Strategic Directions for Improvement 73 5.1 Coordination with the SHRP 2 C04 Project 73 5.2 Breakthrough Directions on the Demand Side 76 5.2.1 Approaches to Accounting for Heterogeneity of Highway Users 77 5.2.2 Travel Segmentation (Observed Heterogeneity) 78 5.2.3 Probabilistic Distribution of VOT and VOR (Unobserved Heterogeneity) 81 5.2.4 Additional Travel Dimensions and Choice Models 83 5.2.5 Incorporation of Travel Time Reliability 84 5.2.6 Modeling Time-of-Day Choice and Peak Spreading 86 5.2.7 Modeling Car Occupancy 87 5.3 Breakthrough Directions on the Network Simulation Side 88 5.3.1 Network Assignment Models and Algorithms in the Context of Pricing 88 5.3.2 Heterogeneity of Users in Traffic Network Assignment and Simulation 90 5.3.3 Perspective of Using TRANSIMS for Highway Pricing Projects 92 5.4 Integration of Demand Model and Network Simulation 94 5.4.1 Essence of Equilibrium and Possible Feedback Options 94 5.4.2 Incorporation of Reliability in Network Equilibrium 95 Chapter 6 Pilot Studies for Demonstration of Improved Tools 97 6.1 Improvement of the San Francisco ABM for Pricing Studies 97 6.1.1 General Model Structure and Phased Improvement 97 6.1.2 Model Structure Improvement for Choice of Tolls 99 6.1.3 Model Estimation and Structural Changes 108 6.1.4 Model Calibration 111 6.1.5 Conclusions 112 6.2 Improvement of the New York ABM for Manhattan Area Pricing Study 113 6.2.1 Objectives of the Study 113 6.2.2 Modeled Options for Area Congestion Pricing 114 6.2.3 Structure of the NYMTC ABM 116 6.2.4 Application Assumptions and Model Adjustments for Area Pricing 118 6.2.5 Application Assumptions and Model Adjustments for License Plate Rationing 120 6.2.6 Aggregation of Model Output for Analysis 121 6.2.7 Technical Lessons Learned 122 6.2.8 Conclusions 123 6.3 Modeling User Response to Pricing with DTA: Baltimore-Washington Corridor 123 6.3.1 Description of the Study 123 6.3.2 Problem Statement 124 6.3.3 Conceptual Framework 125 6.3.4 Multidimensional Dynamic Stochastic User Equilibrium Formulation 128 6.3.5 Solution Algorithm 128 6.3.6 Estimation of Preferred Arrival Time (PAT) Pattern 129 6.3.7 Experimental Results 130 6.3.8 Conclusions 143 6.4 Improvement of the Los Angeles 4-Step Model for Pricing Studies 143 6.4.1 Objectives of the Study and Short-Term Model Enhancements 143 6.4.2 Auto Choices and Utility Functions in Mode Choice 147 6.4.3 Improvements to Highway Assignment 148 6.4.4 Speed Feedback Implementation 148 6.4.5 Time of Day and Peak Spreading Model 149 6.4.6 Calibration and Validation 152 6.4.7 Conclusions 152 Chapter 7 Conclusions and Recommendations for Further Research 153 7.1 Existing Practices and Identified Gaps 153 7.2 Possible Short-Term Improvements 154 7.3 Major Long-Term Improvements and Strategic Directions 155 7.4 Suggestions for Future Research in Adjacent and Related Areas 156 References 158 Appendix A 163