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

2004 Version - Introduction

Microsimulation is the modeling of individual vehicle movements on a second or subsecond basis for the purpose of assessing the traffic performance of highway and street systems, transit, and pedestrians. The last few years have seen a rapid evolution in the sophistication of microsimulation models and a major expansion of their use in transportation engineering and planning practices. These guidelines provide practitioners with guidance on the appropriate application of microsimulation models to traffic analysis problems, with an overarching focus on existing and future alternatives analysis.

The use of these guidelines will aid in the consistent and reproducible application of microsimulation models and will further support the credibility of the tools of today and tomorrow. As a result, practitioners and decision-makers will be equipped to make informed decisions that will account for current and evolving technology. Depending on the project-specific purpose, need, and scope, elements of the process described in these guidelines may be enhanced or adapted to support the analyst and the project team. It is strongly recommended that the respective stakeholders and partners consult prior to and throughout the application of any microsimulation model. This further supports the credibility of the results, recommendations, and conclusions, and minimizes the potential for unnecessary or unanticipated tasks.

Organization of Guidelines

These guidelines are organized into the following chapters and appendixes:

• Introduction (this chapter) highlights the key guiding principles of microsimulation and provides an overview of these guidelines.
• Chapter 1.0 addresses the management, scope, and organization of microsimulation analyses.
• Chapter 2.0 discusses the steps necessary to collect and prepare input data for use in microsimulation models.
• Chapter 3.0 discusses the coding of input data into the microsimulation models.
• Chapter 4.0 presents error-checking methods.
• Chapter 5.0 provides guidance on the calibration of microsimulation models to local traffic conditions.
• Chapter 6.0 explains how to use microsimulation models for alternatives analysis.
• Chapter 7.0 provides guidance on the documentation of microsimulation model analysis.
• Appendix A provides an introduction to the fundamentals of microsimulation model theory.
• Appendix B provides guidance on the estimation of the minimum number of microsimulation model run repetitions necessary for achieving a target confidence level and confidence interval.
• Appendix C provides guidance on the estimation of the duration of the initialization (warmup) period, after which the simulation has stabilized and it is then appropriate to begin gathering performance statistics.
• Appendix D provides examples of some simple manual search algorithms for optimizing parameters during calibration.
• Appendix E summarizes the standard statistical tests that can be used to determine whether two alternatives result in significantly different performance. The purpose of these tests is to demonstrate that the improved performance in a particular alternative is not a result of random variation in the simulation model results.
• Appendix F describes a manual method for constraining external demands to available capacity. This method is useful for adapting travel demand model forecasts for use in microsimulation models.
• Appendix G provides useful references on microsimulation.

Guiding Principles of Microsimulation

Microsimulation can provide the analyst with valuable information on the performance of the existing transportation system and potential improvements. However, microsimulation can also be a time-consuming and resource-intensive activity. The key to obtaining a cost-effective microsimulation analysis is to observe certain guiding principles for this type of analysis:

• Use of the appropriate tool is essential. Do not use microsimulation analysis when it is not appropriate. Understand the limitations of the tool and ensure that it accurately represents the traffic operations theory. Confirm that it can be applied to support the purpose, needs, and scope of work, and can address the question that is being asked.
• Traffic Analysis Toolbox, Volume II: Decision Support Methodology for Selecting Traffic Analysis Tools (Federal Highway Administration (FHWA), presents a methodology for selecting the appropriate type of traffic analysis tool for the task.
• Do not use microsimulation if sufficient time and resources are not available. Misapplication can degrade credibility and can be a focus of controversy or disagreement.
• Good data are critical for good microsimulation model results.
• It is critical that the analyst calibrate any microsimulation model to local conditions.
• Output of a microsimulation model is different from that of the Highway Capacity Manual (HCM) (Transportation Research Board (TRB)). Definitions of key terms, such as "delay" and "queues," are different at the microscopic level of microsimulation models than at the macroscopic level typical of the HCM.
• Prior to embarking on the development of a microsimulation model, establish its scope among the partners, taking into consideration expectations, tasks, and an understanding of how the tool will support the engineering decision. Identify known limitations.
• To minimize disagreements between partners, embed interim periodic reviews at prudent milestones in the model development and calibration processes.

Additional information on traffic microsimulation fundamentals is provided in Appendix A.

Terminology Used in These Guidelines

Calibration: Process where the analyst selects the model parameters that cause the model to best reproduce field-measured local traffic operations conditions.

Microsimulation: Modeling of individual vehicle movements on a second or subsecond basis for the purpose of assessing the traffic performance of highway and street systems.

Model: Specific combination of modeling software and analyst-developed input/parameters for a specific application. A single model may be applied to the same study area for several time periods and several existing and future improvement alternatives.

Project: To reduce the chances of confusing the analysis of a project with the project itself, this report limits the use of the term "project" to the physical road improvement being studied. The evaluation of the impact of a project will be called an "analysis."

Software: Set of computer instructions for assisting the analyst in the development and application of a specific microsimulation model. Several models can be developed using a single software program. These models will share the same basic computational algorithms embedded in the software; however, they will employ different input and parameter values.

Validation: Process where the analyst checks the overall model-predicted traffic performance for PPPra street/road system against field measurements of traffic performance, such as traffic volumes, travel times, average speeds, and average delays. Model validation is performed based on field data not used in the calibration process. This report presumes that the software developer has already completed this validation of the software and its underlying algorithms in a number of research and practical applications.

Verification: Process where the software developer and other researchers check the accuracy of the software implementation of traffic operations theory. This report provides no information on software verification procedures.

Microsimulation Model Development and Application Process

The overall process for developing and applying a microsimulation model to a specific traffic analysis problem consists of seven major tasks:

1. Identification of Study Purpose, Scope, and Approach.
2. Data Collection and Preparation.
3. Base Model Development.
4. Error Checking.
5. Calibration.
6. Alternatives Analysis.
7. Final Report and Technical Documentation.

Each task is summarized below and described in more detail in subsequent chapters. A flow chart, complementing the overall process, is presented in Figure 1. It is intended to be a quick reference that will be traceable throughout the document. This report's chapters correspond to the numbering scheme in Figure 1.

Figure 1. Microsimulation model development and application process.

To demonstrate the process, an example problem is also provided. The example problem involves the analysis of a corridor consisting of a freeway section and a parallel arterial. For simplicity, this example assumes a proactive traffic management strategy that includes ramp metering. Realizing that each project is unique, the analyst and project manager may see a need to revisit previous tasks in the process to fully address the issues that arise.

Organization and management of a microsimulation analysis require the development of a "scope" for the analysis. This scope includes identification of project objectives, available resources, assessment of verified and available tools, quality assurance plan, and identification of the appropriate tasks to complete the analysis.

Task 1: Microsimulation Analysis Organization/Scope

The key issues for the management of a microsimulation study are:

• Securing sufficient expertise to develop and/or evaluate the model.
• Providing sufficient time and resources to develop and calibrate the microsimulation model.
• Developing adequate documentation for the model development process and calibration results.

Task 2: Data Collection and Preparation

This task involves the collection and preparation of all of the data necessary for the microsimulation analysis. Microsimulation models require extensive input data, including:

• Geometry (lengths, lanes, curvature).
• Controls (signal timing, signs).
• Existing demands (turning volumes, origin-destination (O-D) table).
• Calibration data (capacities, travel times, queues).
• Transit, bicycle, and pedestrian data.

In support of tasks 4 and 5, the current and accurate data required for error checking and calibration should also be collected. While capacities can be measured at any time, it is crucial that the other calibration data (travel times, delays, and queues) be gathered simultaneously with the traffic counts.

Task 3: Base Model Development

The goal of base model development is a model that is verifiable, reproducible, and accurate. It is a complex and time-consuming task with steps that are specific to the software used to perform the microsimulation analysis. The details of model development are best covered in software-specific user's guides, and, for this reason, the development process may vary. This report provides a general outline of the model development task.

The method for developing a microsimulation model can best be thought of as the building up of several layers of the model until the model has been completed. The first layer (the link/node diagram) sets the foundation for the model. Additional data on traffic controls and link operations are then added on top of this foundation. Travel demand and traveler behavior data are then added to the basic network. Finally, the simulation run control data are input to complete the model development task. The model development process does not have to follow this order exactly; however, each of these layers is required in some form in any simulation model. The model development task should also include the development and implementation of a quality assurance/quality control (QA/QC) plan to reduce the introduction of input coding errors into the model.

Task 4: Error Checking

The error-checking task is necessary to identify and correct model coding errors so that they do not interfere with the model calibration task. Coding errors can distort the model calibration process and cause the analyst to adopt incorrect values for the calibration parameters. Error checking involves various tests of the coded network and the demand data to identify input coding errors.

Task 5: Microsimulation Model Calibration

Each microsimulation software program has a set of user-adjustable parameters that enable the practitioner to calibrate the software to better match specific local conditions. These parameter adjustments are necessary because no microsimulation model can include all of the possible factors (both onstreet and offstreet) that might affect capacity and traffic operations. The calibration process accounts for the impact of these "unmodeled" site-specific factors through the adjustment of the calibration parameters included in the software for this specific purpose.

Therefore, model calibration involves the selection of a few parameters for calibration and the repeated operation of the model to identify the best values for those parameters. This can be a time-consuming process. It should be well documented so that later reviewers of the model can understand the rationale for the various parameter changes made during calibration. For example, the car-following sensitivity factor for a specific freeway segment (link 20 to 21) has been modified to a value of 95 to match the observed average speed in this freeway segment.

The key issues in calibration are:

• Identification of necessary model calibration targets.
• Allocation of sufficient time and resources to achieve calibration targets.
• Selection of the appropriate calibration parameter values to best match locally measured street, highway, freeway, and intersection capacities.
• Selection of the calibration parameter values that best reproduce current route choice patterns.
• Calibration of the overall model against overall system performance measures, such as travel time, delay, and queues.

Task 6: Alternatives Analysis With Microsimulation Models

This is the first model application task. The calibrated microsimulation model is run several times to test various project alternatives. The first step in this task is to develop a baseline demand scenario. Then the various improvement alternatives are coded into the simulation model. The analyst then determines which performance statistics will be gathered and runs the model for each alternative to generate the necessary output. If the analyst wishes to produce HCM level-of-service (LOS) results, then sufficient time should be allowed for post-processing the model output to convert microsimulation results into HCM-compatible LOS results.

The key issues in an alternatives analysis are:

• Forecasting realistic future demands.
• Selecting the appropriate performance measures for evaluation of the alternatives.
• Accurate accounting of the full congestion-reduction benefits of each alternative.
• Properly converting the microsimulation results to HCM LOS (reporting LOS is optional).

Task 7: Final Report/Technical Documentation

This task involves summarizing the analytical results in a final report and documenting the analytical approach in a technical document. This task may also include presentation of study results to technical supervisors, elected officials, and the general public.

The final report presents the analytical results in a form that is readily understandable by the decision-makers for the project. The effort involved in summarizing the results for the final report should not be underestimated, since microsimulation models produce a wealth of numerical output that must be tabulated and summarized.

Technical documentation is important for ensuring that the decision-makers understand the assumptions behind the results and for enabling other analysts to reproduce the results. The documentation should be sufficient so that given the same input files, another analyst can understand the calibration process and repeat the alternatives analysis.