Traffic Impact Study Improvements: Part 5 – When is a Trip Not a Trip?

Guest Post by Bryant Ficek, PE, PTOE, Vice President at Spack Consulting

Earlier this year, I detailed how our standard process for a Traffic Impact Study has several points of assumptions at best or guesses at worst. This post continues that discussion.  Check out the “Top 6 Ways to Pick Apart a Traffic Study” for more on the general topic and expect more posts to follow on this subject.

Trip generation is the process of estimating the amount of traffic a proposed development will have once it is built and operating. Trip distribution is the process by which we take the raw projected traffic for a development (trip generation) and add it to the existing volumes on the transportation network. The step in-between is determining whether all the trip generation will be new to the roadway.

To start with, there are several types of trips as follows (with definition summarized from the Institute of Transportation Engineers or ITE). The figure below illustrates the different types of trips.

• Primary or New. Traffic with the specific purpose of visiting the site being studied.
• Pass-By. Traffic already on the way from an origin to a primary trip destination that will make an intermediate stop at the site being studied without a route diversion.
• Diverted. Traffic attracted to the site being studied from adjacent facilities without direct access to the site. A diverted trip example is a through trip on a freeway that diverts to an exit and a development, adding traffic to the local road but removing traffic from the freeway.
• Internal. Traffic associated with multi-use developments where trips among various land uses can be made on the site being studied without using the major street system. These trips can be made either by walking or by vehicles using internal roadways.

These different trip generation options, combined with so many different types of land uses, leads to virtually limitless possibilities for the amount and type of traffic a particular site could generate on the roadway system. As with our trip distribution column, we initially thought about testing multiple scenarios, which would be relatively easy with today’s software. At least, theoretically. To restate our collective conclusion – While interesting on a pure research level, a thicker actual traffic impact study report covering multiple results leads us down a path no one wants to go.

Furthermore, sub-dividing the raw trip generation into parts is not something that can be quantified into a “one-size fits all” equation. Given the possibilities and the limits of our collective traffic research to date, ITE provides the best procedure to follow. So this article is dedicated to reviewing that procedure, which is spelled out in ITE’s Trip Generation Handbook and Trip Generation Manual, Volume 1. That step-by-step process is as follows:

1. Raw Trip Generation. Using ITE or other land use information (try tripgeneration.org!), calculate the raw trip generation for the site.
2. Internal Reductions. If a multi-use site, apply a reduction to account for traffic between the different land uses that does not access the surrounding roadway system. ITE has a nine step process for internal reductions, which can be accomplished through their spreadsheet tool. I am providing a copy of the Internal Trip Generation spreadsheet we created and use at Spack Consulting. It’s a simple tool based on Chapter 7 of the Trip Generation Handbook. Click the button to download a copy.  
3. Pass-By and Diverted Number of Trips. Use either local data or ITE data to determine a percentage of the reduced trip generation that is pass-by or diverted. Similar to the ITE Trip Generation data, both pass-by and diverted trip percentages are available by average rate or an equation for many land uses. Use this percentage to calculate the total pass-by and diverted trips for the site.
4. Pass-By and Diverted Trip Patterns. Use the existing traffic to determine how the pass-by and diverted trips will access the site.
5. Pass-By and Diverted Trip Volume Adjustment. Apply the existing traffic patterns to the pass-by and diverted trips to establish the impact on the roadway system for these trips.
6. Remaining Primary/New trips. Determine the remaining trip generation after reducing for internal trips and then removing the pass-by and diverted trips.
7. Primary/New Trip Pattern. We discussed factors to consider for the primary/new trip distribution in Part 4 of this series.
8. Primary/New Trip Volume Adjustment. Apply the trip distribution to the primary/new trips to determine the impact on the roadway system for these trips.
9. Final Volumes. Combine the pass-by, diverted, and primary/new trips at each study intersection to determine the final impact of the site being studied.

We can demonstrate this process on a theoretical study site with the following characteristics:

• 17,000 square feet of office, 3,000 square feet of fast food with a drive-thru, and 10 vehicle fueling positions at a gas station with convenience market
• One driveway accesses the site off a busy road (1,000 vehicles in the p.m. peak hour)
• A highway interchange with the busy road is located just east of the site

1. Trip Generation (PM Peak)

• General Office, Land Use 710 – 98 raw trips
• Fast Food with Drive Thru, Land Use 934 – 98 raw trips
• Gas Station with Convenience Market, Land Use 945 – 136 raw trips

2. Internal Trips

3.  Pass-by and Diverted Trips

4. Pass-By and Diverted Patterns (per the theoretical roadway data)

5. Pass-By and Diverted Trip Volume Adjustment

6. Remaining Primary/New trips:

• Office – (98 raw – 5 internal – 0 pass-by – 0 diverted) = 93 primary/new trips
• Fast Food – (98 raw – 21 internal – 43 pass-by – 23 diverted) = 11 primary/new trips
• Gas Station – (136 raw – 22 internal – 57 pass-by – 26 diverted) = 31 primary/new trips

7.  Primary/New Trip Pattern (per knowledge of theoretical area)

8.  Primary/New Trip Volume Adjustment

9.  Final Volumes (add the pass-by, diverted, and primary/new trips together)

We don’t include all of the above example graphs in our reports. Instead, our short-hand method is a trip generation table that looks like this:

As a final note, the internal, pass-by, diverted, and new percentages are often adjusted from the base ITE information. ITE itself notes the limited amount of data available and the inherent variability in surveyed sites. The best approach, if possible, is to discuss the percentages with the governing agency to achieve agreement and buy-in before you get too far down the path in your analysis.

Did you miss the other installments of the Traffic Impact Study Improvements series? Here are the links to the other articles:

1. Part 1 – Traffic Counts
2. Part 2 – Would Multiple Results Help Us?
3. Part 3 – All Trips are Equal, But Some Trips are More Equal Than Others
4. Part 4 – 8 Considerations When Generating Trip Distribution Patterns