Transportation modeling applications can be divided into two categories: travel demand forecasting and operational modeling. Demand forecasting predicts future traffic volumes for long-term infrastructure investments, while operational modeling focuses on specific problems at a near-term or finer level of detail (such as improving the traffic signal timing along a corridor, identifying the causes of an existing bottleneck, assessing the mobility impacts of a planned construction project, decision making on alternative selection, and more). The tools and methodologies used for the two types of modeling are different, with demand forecasting using macroscopic models and operational modeling using various traffic simulation modeling software. While processes and technical standards for travel demand modeling have been well documented in the previous literature, there is limited information on state departments of transportation (DOTs) practices for operational simulation modeling.
The objective of this synthesis project is to document state DOT processes and procedures for operational traffic simulation models.
Information to be gathered includes (but is not limited to):
The extent to which DOTs use traffic simulation models;
o Administrative procedures or protocols that mandate or restrict the use of simulation models, e.g., legislative code, agency policies, etc.
o Usage of traffic simulation models by staff or contractors
2. Skill set development within the agency (staff training etc.) of the policy and procedure as well as simulation software;
3. The typical applications of specific traffic simulation models, for example design, corridor studies, work zone planning, etc;
o Type of the project
o type of the software including specialized features and companion tools
4. Methods and guidelines for the development, implementation and quality control of simulation models (including calibration, validation, review), and maintenance/archiving;
5. Factors to consider for model scoping;
o Procedures and policies
o Funding and scheduling constraints,
o Geographic extent,
o Travel conditions, and
o Temporal extent of models.
6. Data collection/acquisition practices;
o Data sources used as inputs for operational models (such as probe data, regional travel demand forecasting model outputs, etc.); and
o The age of data and the frequency of updating the data inputs;
o Data fusion.
7. Model performance review practices
o Return on investment (qualitative and quantitative)
o Model reuse and adaptation
o Post-construction verification
Information will be gathered through a literature review, a survey of state DOTs, and follow-up interviews with selected DOTs for the development of case examples. gaps and suggestions for research to address those gaps will be identified.
Information Sources (Partial):
Relevant background information can be found in the forthcoming Transportation Systems Simulation Manual (TSSM) and in the FHWA Traffic Analysis Toolbox series.
First Panel: October 5, 2023, Washington, D.C.
Teleconference with Consultant: November 3, 2023, 1:00- 2:00 pm EST
Second Panel: June 18, 2023, Washington, D.C.