2019 VERSION: Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software 2019 Update to the 2004 Version

2004 Version - Table of Contents

Foreword

Introduction

• Organization of Guidelines
• Guiding Principles of Microsimulation
• Terminology Used in These Guidelines
• Microsimulation Model Development and Application Process

1.0 Microsimulation Study Organization/Scope

• 1.1 Study Objectives
• 1.2 Study Breadth
• 1.3 Analytical Approach Selection
• 1.4 Analytical Tool Selection (Software)
  • 1.4.1 Technical Capabilities
  • 1.4.2 Input/Output/Interfaces
  • 1.4.3 User Training/Support
  • 1.4.4 Ongoing Software Enhancements
• 1.5 Resource Requirements
• 1.6 Management of a Microsimulation Study
• 1.7 Example Problem: Study Scope and Purpose

2.0 Data Collection/Preparation

• 2.1 Required Data
  • 2.1.1 Geometric Data
  • 2.1.2 Control Data
  • 2.1.3 Demand Data
• 2.2 Calibration Data
  • 2.2.1 Field Inspection
  • 2.2.2 Travel Time Data
  • 2.2.3 Point Speed Data
  • 2.2.4 Capacity and Saturation Flow Data
  • 2.2.5 Delay and Queue Data
• 2.3 Data Preparation/Quality Assurance
• 2.4 Reconciliation of Traffic Counts
• 2.5 Example Problem: Data Collection and Preparation

3.0 Base Model Development

• 3.1 Link-Node Diagram: Model Blueprint
• 3.2 Link Geometry Data
• 3.3 Traffic Control Data at Intersections and Junctions
• 3.4 Traffic Operations and Management Data for Links
• 3.5 Traffic Demand Data
• 3.6 Driver Behavior Data
• 3.7 Events/Scenarios Data
• 3.8 Simulation Run Control Data
• 3.9 Coding Techniques for Complex Situations
• 3.10 Quality Assurance/Quality Control (QA/QC) Plan
• 3.11 Example Problem: Base Model Development

4.0 Error Checking

• 4.1 Review Software Errors
• 4.2 Review Input
• 4.3 Review Animation
• 4.4 Residual Errors
• 4.5 Key Decision Point
• 4.6 Example Problem: Error Checking

5.0 Calibration of Microsimulation Models

• 5.1 Objectives of Calibration
• 5.2 Calibration Approach
• 5.3 Step 1: Calibration for Capacity
  • 5.3.1 Collect Field Measurements of Capacity
  • 5.3.2 Obtain Model Estimates of Capacity
  • 5.3.3 Select Calibration Parameter(s)
  • 5.3.4 Set Calibration Objective Function
  • 5.3.5 Perform Search for Optimal Parameter Value
  • 5.3.6 Fine-Tune the Calibration
• 5.4 Step 2: Route Choice Calibration
  • 5.4.1 Global Calibration
  • 5.4.2 Fine-Tuning
• 5.5 Step 3: System Performance Calibration
• 5.6 Calibration Targets
• 5.7 Example Problem: Model Calibration

6.0 Alternatives Analysis

• 6.1 Baseline Demand Forecast
  • 6.1.1 Demand Forecasting
  • 6.1.2 Constraining Demand to Capacity
  • 6.1.3 Allowance for Uncertainty in Demand Forecasts
• 6.2 Generation of Alternatives
• 6.3 Selection of Measures of Effectiveness (MOEs)
  • 6.3.1 Candidate MOEs for Overall System Performance
  • 6.3.2 Candidate MOEs for Localized Problems
  • 6.3.3 Choice of Average or Worst Case MOEs
• 6.4 Model Application
  • 6.4.1 Requirement for Multiple Repetitions
  • 6.4.2 Exclusion of Initialization Period
  • 6.4.3 Avoiding Bias in the Results
  • 6.4.4 Impact of Alternatives on Demand
  • 6.4.5 Signal/Meter Control Optimization
• 6.5 Tabulation of Results
  • 6.5.1 Reviewing Animation Output
  • 6.5.2 Numerical Output
  • 6.5.3 Correcting Biases in the Results
• 6.6 Evaluation of Alternatives
  • 6.6.1 Interpretation of System Performance Results
  • 6.6.2 Hypothesis Testing
  • 6.6.3 Confidence Intervals and Sensitivity Analysis
  • 6.6.4 Comparison of Results to the HCM
• 6.7 Example Problem: Alternatives Analysis

7.0 Final Report

• 7.1 Final Report
• 7.2 Technical Report/Appendix

Appendix A: Traffic Microsimulation Fundamentals

• A.1 Overview
• A.2 System Update Mechanism
• A.3 Traffic Stream Representation
• A.4 Randomness in Traffic Flow
• A.5 Microsimulation Process

Appendix B: Confidence Intervals

• B.1 Why Are Multiple Model Runs Required?
• B.2 Estimation of Sample Standard Deviation
• B.3 Selection of Desired Confidence Level
• B.4 Selection of Desired Confidence Interval

Appendix C: Estimation of the Simulation Initialization Period

Appendix D: Simple Search Algorithms for Calibration

• D.1 Single-Parameter Search Algorithm (Golden Section)
• D.2 Simple Two-Parameter Search Algorithm
• D.3 Dual-Objective, Two-Parameter Search Algorithm

Appendix E: Hypothesis Testing of Alternatives

• E.1 Estimation of the Required Number of Model Repetitions
• E.2 Hypothesis Testing for Two Alternatives
• E.3 Hypothesis Testing for Multiple Alternatives
• E.4 What To Do If the Null Hypothesis Cannot Be Rejected

Appendix F: Demand Constraints

Appendix G: Bibliography

• G.1 Traffic Microsimulation Fundamentals
• G.2 Calibration and Validation of Microsimulation Models
• G.3 Analysis of Results