Screen shot of Transmodeler traffic signal timing.

Building More Accurate Traffic Modeling for Twin Cities Construction Projects

MnDOT is exploring different software options for developing a “mesoscopic dynamic traffic model” that can more accurately predict road construction impacts than current macroscopic models like the Twin Cities Regional Travel Demand Forecasting Model.

“Dynamic traffic assignment is an emerging model type, and there are a lot of software platforms with different methodologies. MnDOT was interested in reviewing their pros
and cons,” said Jim Henricksen, Traffic Forecaster, MnDOT Metro District, who helped lead a recent research project that analyzed different software packages.

“A team maintains the Twin Cities Regional Travel Demand Forecasting Model. Any mesoscopic model would require a similar maintenance effort to keep the model from becoming obsolete as construction adds new lanes,” said John Hourdos, Director, Minnesota Traffic Observatory, University of Minnesota, and principal investigator for the study.

What Was the Need?

Traffic modeling is a valuable tool used in transportation planning to predict the impacts of new construction or maintenance projects. MnDOT currently has modeling tools available in two scales: macroscopic and microscopic. Macroscopic-scale planning level tools such as the Twin Cities Regional Travel Demand Forecasting Model predict driver route choice and the number of drivers that will travel on a given road at a given time. Microscopic-scale traffic simulation, on the other hand, models driver behaviors such as gap acceptance or acceleration rates. MnDOT uses microscopic-scale simulation to plan capacity-increasing projects, but the tool is only feasible on the corridor level because generating the simulation requires a large amount of data and computing power.

To bridge these two scales, MnDOT is developing a mesoscopic-scale dynamic traffic assignment (DTA) model for the Twin Cities. This model falls between microscopic- and macroscopic-scale modeling in scope and complexity. It simulates the movement of individual vehicles based on traffic flow equations rather than driving rules, which requires less detail and computing time than a microscopic simulation and can be used over a wider area. MnDOT will use this model for applications such as staging construction seasons to minimize the disruption caused by multiple large projects, or coordinating traffic modeling across the road networks operated by MnDOT, counties and cities.

To assist in developing this system, MnDOT needed information about the capabilities of available modeling software packages in addition to the needs, desires and restrictions of the agencies and consultants who will be using the model.

What Was Our Goal?

The goal of this project was to better understand the capabilities of commercially avail-able modeling software packages to address MnDOT’s modeling and simulation needs.

What Did We Do?

Investigators interviewed stakeholders about their understanding of and need for mesoscopic traffic simulation and DTA. Stakeholders included individuals who have used or requested data from the Twin Cities Regional Travel Demand Forecasting Model maintained by the Metropolitan Council. Investigators also reviewed four case studies of mesoscopic DTA models used in Manhattan; San Francisco; Detroit; and Jacksonville, Florida.

To supplement the findings from the interviews and case studies, investigators conducted a comprehensive review of the claimed capabilities of six commercially avail-able traffic simulation software packages: TransModeler, Aimsun, DynusT/DynuStudio, Dynameq, Cube Avenue and Vissim. Investigators didn’t test the software, but instead reviewed manufacturers’ documentation and literature to identify limitations of their methods and whether those methods are applicable to MnDOT’s needs.

Traffic in a highway work zone.
DTA can aid in staging multiple major construction projects in the Twin Cities to minimize the disruption they cause to travelers.

What Did We Learn?

To compare the capabilities of the various simulation software packages, investigators created a matrix that included comprehensive notations about a software package’s claimed features that may not fully meet MnDOT’s simulation needs. For example, some software packages claim to model actuated signals, but they create models based on Highway Capacity Manual assumptions rather than real-world conditions.

DynusT is the most commonly used simulation program, possibly because it is open-source and the easiest software to use, although it requires DynuStudio, a commercial graphical user interface and data management system. DynusT also has some limitations, such as not considering the individual lanes in each roadway segment, which would limit its effectiveness in modeling roads where individual lanes have imbalanced densities.

Most interviewees had only limited experience with mesoscopic modeling. Incorporating traffic signals in a simulation network is a significant challenge, according to interviewees, because currently a database of signal timings isn’t available.

While all four of the DTA case studies reviewed required more data, calibration and validation than older models, each of the developers reported that these challenges had been mitigated, and the models created could answer complex questions that previous models couldn’t.

What’s Next?

Traffic simulation and modeling is a fast-developing field, particularly mesoscopic-scale modeling. Each of the software packages reviewed in this project has had at least two new versions in the past 18 months, and while their modeling approaches are fundamental to the software in some cases, in other cases capabilities will be added or improved as software develops.

The foundation of a mesoscopic model for the Twin Cities has been built and tested in Transmodeler (with significant pro bono work from the software developer). However, MnDOT has also used its existing DynusT model for several projects beyond its initial purpose, and the agency will use the information gathered in this project to determine which approach is more practical for MnDOT and its consultants based on cost, capabilities and data availability. Transmodeler is generally more powerful, but it will also incur greater costs, particularly since every consultant would need to acquire its own copy of the software.


This Technical Summary pertains to Report 2017-10, “Framework and Guidelines for the Development of a Twin Cities Mesoscopic DTA Model,” published April 2017.

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