May 2018


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Summer Interns
Water Bug Sampling
Travel Demand Models “101”

Green Infrastructure Seminar

Welcome Summer Interns!

The MACC is lucky to have five incredibly talented people spending their summers with us! Starting from the left to, we have Bethany Heerspink who recently graduated with a degree in Biology from GVSU, Joe Spelde a graduate of Point Loma Nazarene University in San Diego where he studied Political Science, Luke Pommerening who is attending Michigan State for Geology, Quinlan Ferber is attending GVSU for Geography, and Claire Thomassen, also a GVSU student, is studying Geology.

Thank you, interns, for helping us this summer on so many projects!


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Water Bug Sampling: DATE CHANGE

Meet at Adams Street Lansing at 8:30 am, form teams, and carpool to various stream locations. All equipment will be provided, but volunteers are encouraged to bring waders or mud boots if you have them. Ages teens and up and anyone under 16 must be accompanied by an adult. Your RSVP is required to the MACC office: 616-395-268 or

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Upcoming Holland Travel Demand Model  

Written by Jon Roberts – MDOT

MPOs are required to have an objective method to evaluate the federal aid road system as part of their Long Range Transportation Plan or LRTP. The objective method we use in Michigan are Travel demand models. Most small MPO’s generally have very limited staff resources so MDOT holds the models for the Small MPOs which are Metropolitan areas with a population of 50,000 – 200,000.

A travel demand model is a series of mathematical equations which are used to estimate traffic conditions for a given analysis year.  It is based on average travel characteristics of a household stratified by household characteristics such as the number of people, workers, children and vehicles in the household. Travel demand models are designed for system-wide analysis.  They help us predict how changes in the network, or road system, will affect traffic flows.

Travel demand models are developed as a forecasting tool. We use them to predict how future changes in Socio-Economic data, commonly referred to as SE-data, affect traffic flows.  We also use them to predict future traffic congestion and to test solutions for that congestion.

Travel demand models are also used for congestion management.  MPOs long-range transportation plans may include maps of the corridors that are congested.  We define segments or corridors that have a volume over capacity ratio greater than one as congested.  The capacity we use represents the amount of traffic that is comfortable for the area.  So if the volume exceeds the capacity then the road is congested.

MPOs use this information as they develop their project lists for the LRTP. In looking at ways to alleviate congestion we can analyze more than just widening the congested roads.  We can also look at things like improving parallel corridors, improving connectivity which gives drivers an alternate route. Although the signal timing and access management can help a lot with congestion they cannot be modeled using a travel demand model.

The model assigns trips to the network that can be quantified as model volumes.  Other outputs that are helpful in comparative analysis between changes in the road system or future forecasts can then be calculated such as:

  • Volume changes
  • Growth Factors
  • Vehicle Miles Traveled
  • Vehicle Hours Traveled
  • Volume to Capacity Ratios

Travel demand models were designed for the analysis of a transportation system and how it performs as a whole.   Travel demand models are very useful for analysis of travel patterns, growth factors, and comparative analysis.  Although the modal assigns a specific volume to each segment in the model network, values at this level need to be used with caution as they are used for system-wide analysis and depict patterns of changes, not necessarily specific numbers.

The model inputs such as Socio-Economic data and network attributes are developed in conjunction with, reviewed and approved by the MPO committee as part of their LRP process. For the upcoming MACC model, MDOT staff developed 2015 estimations for population, group quarters, and household data based on the 2010 Census Block data and the 2015 ACS estimates.  The block totals were then aggregated by Traffic Analysis Zone (TAZ) and put into a spreadsheet with an identifying field for TAZ number that corresponds to the TAZ ID on maps that MDOT also produced for each jurisdiction.  MDOT also provided spreadsheets of the employment database with a listing for each business and a corresponding TAZ number.  Jon Roberts of MDOT explained the review process and asked that the jurisdiction’s comments be submitted by March 12th. The MACC MPO also passed out envelopes so that the jurisdictions could mail back their materials to them once they had been edited/reviewed.

Upon completion of the data review, MDOT incorporated the local input and updated the population and household data in the TAZ database (used in the travel demand model).  MDOT also updated the employment point file, aggregating the employee numbers by type for each TAZ in the TAZ database. A similar process is required for the future year SE-data of the model. The upcoming MACC model will have a horizon year of 2045.  This year was determined because of the need to maintain a 20-year horizon throughout the life of the LRTP.

Upon calibration of the model, capacity projects can be tested through the model. A capacity project is anything that would either improve or diminish the capacity of a road.  Such as adding lanes, roads or ramps or re-striping a road segment that is four lane to a two-lane road with a continuous turn lane. All capacity projects need to be in the MPOS long-range plan which has at least a 20-year horizon and the Transportation Improvement Program or TIP which has a four-year horizon. All future capacity projects listed in the TIP or LRP must be modeled in forecasts.

For more information on the MACC model or model development process, please contact:

Jon Roberts at

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