Practices for Operational Traffic Simulation Models (2025)
Chapter: Summary
SUMMARY
Practices for Operational Traffic Simulation Models
Traffic simulation modeling is one tool used by many state departments of transportation (DOTs) to improve the operations of their transportation systems. Operational traffic simulation models can be used to facilitate the planning, design, and real-time operations of transportation systems. They can vary in temporal and spatial resolutions but typically focus on solving problems at a specific location at a near-term time horizon (e.g., improving the traffic signal timing along a corridor, identifying the causes of an existing bottleneck, assessing the mobility impacts of a planned construction project, or facilitating decision-making on alternative selection). Although the use of traffic simulation models is commonplace across many DOTs, there are differences in how DOTs implement these models. Therefore, there is a need to enhance the understanding of how DOTs create, calibrate, use, and report information from traffic simulation models.
The objective of this synthesis was to review and document DOT practices regarding the use of operational traffic simulation models. The synthesis scope included various topics related to operational traffic simulation models, such as extent of use, typical applications, software, modeling processes, data sources, and skill set development (e.g., training).
Attainment of the synthesis objectives involved the following major tasks: a literature review, a survey, and follow-up interviews. Various sources, including guidance documents (general and DOT-specific), research reports, journal articles, and other resources were reviewed and synthesized. An online survey questionnaire was distributed to all 50 state DOTs as well as the District of Columbia DOT. The survey included 25 questions on topics such as extent of use, staffing, applications, modeling resolution, software, data sources, use of guidance and other resources, modeling practices, measures of effectiveness (MOEs), and deliverables. Survey responses were received from 49 DOTs, a response rate of 96%. After completion of the survey, follow-up interviews to develop case examples were conducted with the DOTs of Colorado, Indiana, South Carolina, Texas, Virginia, and Washington.
The synthesis findings indicate that use of operational traffic simulation models is prevalent among DOTs, but they are typically reserved for more complex situations that cannot be adequately analyzed using other tools. All 49 of the state DOTs that responded to the survey employ operational traffic simulation models. The need to use operational traffic simulation models is often determined on a project-specific basis. Eighteen of the responding DOTs require approval for the use of operational traffic simulation models on each project. In some cases, scoping meetings at the beginning of a project provide an opportunity to discuss whether the use of traffic simulation models is appropriate.
DOTs use operational traffic simulation models for a wide range of applications. At least 35 DOTs use operational traffic simulation models to some extent for each of the following applications: signal retiming analyses, freeway design alternatives analyses, arterial design
alternatives analyses, traffic impact analyses, and design visualization and communication. Of these applications, operational traffic simulation models are most often used for freeway design alternative analyses, mixed design alternative analyses, and signal retiming analyses. Seven of the responding DOTs use operational traffic simulation models for evacuation route analyses. Twenty-three of the responding DOTs use operational traffic simulation models most frequently for freeways.
Examples of specific applications of operational traffic simulation models include but are not limited to the following: connected and automated vehicles (CAVs); environmental and planning stages of projects (e.g., development of environmental impact statements and modeling for noise, emissions, and fuel consumption); complex interchanges and interchanges with high arterial flow; evaluation of alternatives for intersection layout, lane configuration, storage lengths, and signal operations; performance of traffic analysis for Interstate Access Reports and Interchange Modification Reports; maintenance of traffic analysis for work zone traffic control scenarios; truck climbing lanes; roundabouts; oversaturated conditions; multimodal contexts (e.g., pedestrian signal timing, light rail); and other situations that simpler tools do not handle appropriately. The specialized application used by the highest number of DOTs is signal optimization (38 of the responding DOTs). The specialized application used by the lowest number of DOTs is CAV analysis (three of the responding DOTs).
Resources on operational traffic simulation models are available from FHWA and from state DOTs. FHWA’s resources cover topics such as tool selection, modeling guidance, multiresolution modeling (MRM), and use of simulation for CAV applications. Modeling guidance from FHWA is available through the 2004 Traffic Analysis Toolbox (TAT) Volume III (Dowling et al. 2004), which was updated in 2019 (Wunderlich et al. 2019). The 2019 TAT update includes more detailed guidance on data collection analysis, model calibration, and alternatives analysis and suggests the use of cluster analysis for the identification of travel conditions.
Another general resource (under development by the TRB Standing Committee on Traffic Simulation) is the Transportation System Simulation Manual (TSSM), which provides guidance on topics such as modeling resolutions, scenario development, and modeling processes; it includes case studies with commentary on how to apply the guidance (List 2021).
The literature review conducted for this synthesis identified 21 state DOTs as having one or more published guidelines or other documents detailing traffic simulation. These resources cover topics such as tool selection, project scoping and management, model calibration, and review checklists. Regarding types of resources, responding DOTs have most often developed guidance documents. Other types of resources developed by DOTs include suggested calibration parameters and procedures for model development and review. The availability of documentation regarding (1) the development of procedures for maintenance and the archiving of data or (2) performance studies on the benefits of—or return on investment for—the use of operational traffic simulation models is infrequent.
Synthesis findings indicate that responding DOTs most often use their own state-specific guidance (19 DOTs), followed by ad hoc project-based decisions (15 DOTs) for the calibration of operational traffic simulation models. Six responding DOTs primarily use the 2004 version of the TAT; four responding DOTs primarily employ the 2019 version. Five responding DOTs (those of Missouri, Nevada, New Hampshire, New Mexico, and Oklahoma) use resources from other states (Florida, Oregon, Utah, Virginia, Washington, and Wisconsin). Although there is general movement toward the use of the guidelines in the 2019 TAT, data availability for the cluster analysis is viewed as a significant challenge to broader implementation. Twenty responding DOTs have a process for documenting deviations from modeling guidance on specific projects.
The synthesis also identified practices for modeling processes for operational traffic simulation. Initial scoping meetings are often conducted at the beginning of a project to discuss the project scope and modeling approach. The factors believed to be most important for operational traffic simulation models are (1) justifying the need for simulation analysis, (2) scheduling constraints, (3) level of modeling effort, and (4) data availability. Although nearly all (46) responding DOTs reuse or adapt previously developed operational traffic simulation models to some extent, this practice is only used with a frequency of “usually” or “always” by 13 responding DOTs and simulation models are typically project-specific.
Although operational simulation models can be developed at different resolutions (macroscopic, mesoscopic, microscopic, and multiresolution), the most frequently used simulation modeling resolution is microscopic, followed by macroscopic. Approximately 25% of responding DOTs use hybrid MRM; dynamic traffic assignment is sometimes used on larger projects. Microscopic resolution is most often discussed in the literature, but example applications for other modeling resolutions found in the literature include signal optimization and large-scale evacuation planning (macroscopic); evaluating land development impacts (mesoscopic); and dynamic reversible lane systems and work zones (MRM).
For calibration, most state DOTs with published guidance use variations of the 2004 TAT calibration targets, with slight modifications that frequently reference peer states. The survey results indicate that the following calibration metrics are used, on average, at least occasionally by responding DOTs: volumes, visual inspection, travel times, queue length, intersection level of service (LOS), and freeway density. The calibration metrics used most often by responding DOTs are volumes and visual inspection. Calibration tools and processes can also be found in the existing literature.
DOTs employ various software packages for operational traffic simulation modeling. The software packages used by the highest number of responding DOTs are SimTraffic and Vissim. Twenty-one responding DOTs adopt new versions of operational traffic simulation software at least every two years; the frequency of adopting new software versions can vary depending on the software, schedule, and costs. Consultants often play an active role in the selection of a software tool, and the software deemed most suitable for the specific application is chosen. In some cases, requests for proposals that include traffic simulation requirements will specify the software to be used. Comparisons of software packages in the literature have found that each package has different strengths.
State DOTs compile various datasets for operational traffic simulation models, and 22 responding DOTs fuse data from different sources. The survey results indicate that the most frequently used data sources for operational traffic simulation models are traffic counts, field observations, aerial imagery, and online map data; the data sources used least often are drone footage and transit data. Other data sources include, but are not limited to, travel times, speeds, historical data (for comparison and validation), projection data (for forecasting from the travel demand model count data), subscriptions to vendor data, local agencies, and consultants.
DOT practices for review and documentation of operational traffic simulation models include the use of MOEs, requirements for deliverables, and review procedures (including checklists). For review processes, responding DOTs most often use reviews of performance measures reported from the model, model input data, and animation. A wide range of MOEs are used for both uninterrupted flow and interrupted flow, with speed, travel time, and density LOS most often used for uninterrupted flow and delay or LOS and queue length most often used for interrupted flow. Examples of other methods and measures used to assess model performance include bottlenecks, throughput visual cues, and engineering
judgment. Post-construction verification of operational traffic simulation models is infrequent (indicated by only two responding DOTs).
The deliverables required by the highest number of responding DOTs are a summary of MOEs, simulation model files, a technical memorandum of results, volume diagrams, and a methods and assumptions document that is typically submitted in the early project stages. Twenty-two responding DOTs require all simulation results to be reported with a minimum of 10 simulation seeds.
Eleven DOTs include traffic simulation model review checklists in their guidance. These checklists vary in length, specificity, and content and cover various topics such as network coding; driving behavior; performance measure outputs; calibration thresholds and parameters; and documentation.
DOTs often rely on consultants for the development of operational traffic simulation models, and training is provided through various sources. Most simulation models are developed by consultants with review and oversight from DOT staff. Twenty-seven responding DOTs use consultants for more than 75% of their operational traffic simulation models, and none of the responding DOTs perform all simulation modeling in-house. Some local agencies conduct operational traffic simulation modeling, often using a consultant. Peer reviews are sometimes performed for larger consultant projects, but their use is infrequent. Internal DOT staff members who conduct the development and review of operational traffic simulation models are placed in various divisions, mostly in the areas of operations and design. Eleven responding DOTs have developed training materials for operational traffic simulation models. Training is typically provided by software vendors online and in person; in some cases, in-house training is given.
The synthesis identified challenges faced by state DOTs as well as future growth opportunities for the use of operational traffic simulation models. Challenges faced by DOTs in the use of operational traffic simulation modeling include data availability; cost; staffing limitations; guidance and training needs; difficulty in obtaining and validating data from different sources—especially during the COVID-19 pandemic; diversity of software tools and versions that are used for different types of projects and analyses; archiving and reusing models due to software version changes and project duration; and demonstrating the return on investment for new approaches.
Examples of the ways DOTs are working toward enhancing the use of operational traffic simulation modeling include encouraging consistency in modeling practices; providing more direction on modeling implementation; expanding the use of simulation for multimodal applications (e.g., bicycle, pedestrian, transit, rideshare); applying simulation for safety analysis; continuing the transition to the 2019 TAT; using mesoscopic modeling for transportation systems management and operations alternatives and for regional multimodal mobility programs; adding other software platforms; and increasing the use of MRM. In addition, state DOTs are interested in learning about various aspects of other state DOTs’ experiences with operational traffic simulation models, such as how they approach operational traffic simulation modeling programmatically, their successes, and their struggles.
This synthesis has identified some gaps in existing knowledge as well as future research that would enhance practices for the use of operational traffic simulation models in the United States. Suggestions for future research include the following:
- Creation of guidance—possibly including case examples—that demonstrates the impact of new calibration and data collection recommendations (e.g., comparing the TAT 2004
- and 2019 microsimulation guidance regarding factors such as modeling effort and data requirements) to help demonstrate how the additional effort can lead to greater accuracy and better-informed decisions
- Further development and publication of the TSSM
- Development of national guidance on operational traffic simulation models that could be considered for adoption and use
- Development of additional guidance regarding procedures for maintenance and archiving of data
- Research on the benefits of—or return on investment for—the use of operational traffic simulation models
- Development of guidance and case studies for the use of operational traffic simulation models for safety analyses
- Development of case examples on the use of operational traffic simulation models by metropolitan planning organizations and local agencies
- Development of case examples showing post-construction validation of operational traffic simulation models
- Development and broad dissemination of reviewer training materials for operational traffic simulation models
- Creation of guidance for using artificial intelligence and machine learning to automate the calibration of operational traffic simulation models
- Guidance on how to fuse data sources and leverage existing data for operational traffic simulation models, especially in cases where data availability is limited
- Peer exchange to help state DOTs to exchange information regarding practices for operational traffic simulation models
- Development of a guide for determining best practices and sources of reliable data for incorporating nonmotorized road users into operational traffic simulation models
