Overestimating vehicle traffic hurts housing affordability. Here’s how we can fix it.

January 23, 2019 by Dan Hennessey

Many cities and municipalities envision multi-modal transportation systems as a way to reduce traffic congestion. But at the end of the day, most are still just designing for vehicles.

When developers propose new projects, they are often required to provide a transportation impact analysis (TIA) as a way to assess the impacts of the proposed development on the surrounding transportation network.

Every jurisdiction has its own requirements, but many focus on vehicle capacity at intersections and on roadway segments. Based on the results of TIAs, developers of proposed projects are often required to make improvements (such as widened roads or new traffic signals) as part of the approval process.

That sounds reasonable. What’s the problem?

Trip Generation ManualMost cities assess trip generation with only one variable (density of land use) – despite ample evidence that a number of characteristics affect both person and vehicle trip generation. Trip generation estimates for specific land uses are traditionally gathered from data included in the most current version of a handbook entitled Trip Generation Manual, produced by the Institute of Transportation Engineers (ITE).

We studied 31 locations in Austin, Texas to compare to national trends and construct a model specific to the City. We found that the vehicle trip generation estimates based on the Trip Generation Manual are too high by 52 percent during the AM peak hour and 50 percent during the PM peak hour for the 31 locations. Four of the 31 locations had actual trip counts that were higher than predicted in the AM peak hour, and only one had a trip count that was higher than predicted in the PM peak hour.

Overestimating vehicle trip generation can lead to additional capacity for vehicles that is neither warranted nor consistent with a jurisdiction’s vision for their mobility network. It also increases the cost of development and can color the community’s opinion of a potential development and increase opposition.

We developed a better model.

To remedy this overestimation, BIG RED DOG Engineering developed a vehicle trip generation model specific to the City that accounts for specific characteristics of the development, availability of non-auto modes, and the demographic profile of the surrounding area.

We came up with a new model that considers additional variables (such as WalkScore to reflect connectivity/walkability, household size per ZIP code, average vehicle ownership in ZIP code) and reduced overestimation error from 47% in the AM peak hour and 54% in the PM peak hour using only the ITE data to 9% and 5%, respectively.

In Conclusion

We believe that a version of our model could be replicated for most jurisdictions within the United States. Using a combination of variables in addition to the land use and its intensity, local models can be developed that will allow municipalities, engineers, and planners move toward a more multimodal vision.

Want more details? Download the study (PDF file):

Small Data

Dan presented this paper at the 2018 ITE Joint Western & Texas District Meeting in Keystone, Colorado. The paper was awarded 2018 TexITE Technical Paper Award, which was presented at the TexITE Business Luncheon in November 2018 at the joint meeting of TexITE and ITS Texas. The award recognizes the author(s) of a paper prepared by a non-student member or affiliate of the Texas District.

awards

For more information, contact Dan Hennessey, Director of Transportation Services at BIG RED DOG today.

Written by Dan Hennessey

Dan Hennessey

Dan Hennessey, P.E., PTOE is Director of Transportation Engineering at BIG RED DOG. Dan holds a Master’s Degree in Civil Engineering (Transportation) from the University of California, Berkeley and a Bachelor of Science in Civil Engineering from The Ohio State University. Dan is responsible for managing our Raving Fans and prospective clients, overseeing the performance of our traffic and transportation engineering design staff, steering our marketing strategy, and spearheading our community outreach and volunteer efforts. Dan’s professional experience and expertise focuses on Traffic Impact Analysis (TIA) studies, highway, freeway and arterial operations analysis, signal coordination and synchronization, traffic signal design, travel demand forecasting, and pedestrian and bicycle facility design.