Model forecasts future travel patterns for region

As part of our role as the metropolitan planning organization for the Kansas City region, MARC leads planning, community engagement, inter-jurisdictional coordination, and allocation of federal funding to promote a safe, efficient, equitable and sustainable surface transportation system.

A key tool in this work is a travel demand model that predicts and understands how people travel in the region. It helps planners and policymakers make decisions about transportation infrastructure, such as roads, public transit, and bike lanes.

Think of it as a virtual simulation that considers various factors like population, employment, land use, and transportation options to estimate how many trips people will make and how they will choose to travel. The model considers things like distance, travel time, cost, and personal preferences.

By analyzing this information, the model can forecast future travel patterns and demand for different modes of transportation, such as cars, buses, trains, or walking. This helps determine where and how to invest in transportation improvements to meet the needs of the population, reduce congestion, and improve air quality.

The model helps MARC develop the region’s long-range metropolitan transportation plan, ConnectedKC 2050, a key product of the metropolitan planning process. This plan sets a vision for our future transportation system, adopts policies and strategies, and ultimately identifies regionally significant projects to help achieve our regional vision.

The current MARC travel demand model is an enhanced four-step, trip-based model that focuses on daily travel patterns.

In recent years, MARC has made significant improvements to the model, including an auto availability model, income and household size sub-models, and enhanced trip distribution procedures that include destination choice formulations. Furthermore, a time-of-day component has been added to model 24 one-hour daily time slices, and the KCI Airport has been included as a special generator.  

The model is implemented using EMME transportation modeling software package. It has been calibrated to a base year of 2019 and contains future-year data that reflects forecasted 2050 conditions.