February 2


Trip Generation: Average Rate vs. Regression Curve

By Mike Spack

February 2, 2011

MN Traffic Engineer, Traffic Impact Study Trip Generation Rochester

Here's a question from Gary Shannon (City Traffic Engineer, Rochester, MN) and my response regarding typical use of the Institute of Transportation Engineers' Trip Generation report. 

Gary's Question about the use of Trip Generation's Average Rate vs. Regression Curve

We have a situation in Rochester concerning a trip generation estimate for a development that is being opposed by a neighborhood.  At issue is whether the average trip generation rate or the equation be used to determine the daily trips.  (The value being determined happens to fall near one end of the plotted data points).

Would you, as friends and peers in this discipline, please provide me with an explanation concerning the practice within the reviewing government agencies that you are familiar with that is generally  followed concerning the rate that is used?  This item is going before the City Council next Monday, so if I could hear back from you in the next couple days it would be much appreciated.

My Answer

The majority (almost all) of the traffic studies I’ve produced and have reviewed in my career in Minnesota have used the average trip generation rate instead of the supplied regression equations to calculate trip generation for developments.  The hurdle for using the regression equation is quite high based on the Institute of Transportation Engineers’ Trip Generation Handbook, 2nd Edition, which recommends using the regression equation only when the data sample has at least 20 data points AND an R2 value of 0.75 or higher. 

Caveat to allow for the engineer’s judgment – we’re supposed to look at the data plot, find the cluster of developments that are sized similarly to our study development, and consider using the fitted line (average rate or regression) that best matches the cluster of trip generation values.  A further caveat to all of this – if the proposed development size lies on the extreme high or low end of the data plot, performing an independent trip generation study of similarly sized/local developments to determine local trip generation characteristics should be considered.

  • Does anyone know what ITE means, when it says to use the Regression Equation:
    standard deviation > 110% of weighted average rate?
    In my experience, the standard deviation is almost always smaller than the average rate.

  • At the heart of it, if the standard deviation is larger than the weighted average it means there is a big spread in the data (someone please correct me if my recollection of stats from 15+ years ago is wrong). I don’t know how they picked 110% as the magic number. I think the R Squared value related to the regression equation is more important. The first two rules I quoted make more sense to me as a practitioner.
    A random flip through of the Trip Generation report came up with most data sets not meeting the 110% rule, however I noticed a few of the housing categories did.

  • I also received that email from Gary. My response to him was as follows:
    “My experience has been that the decision on whether to require rate or allow use of the equation varies by agency. It seems like the more “progressive” agencies will allow use of the equation while some will only accept the rate.
    “The guidance provided by ITE on whether to use average rate or fitted curve equation is covered in their supporting guide to Trip Generation, titled Trip Generation Handbook. The current edition of this text is the 2nd Edition, published in 2004. Page 10 provides a handy flow chart that gives guidance on whether to use the average rate, fitted curve equation, or to collect local data. The nearby pages (pp. 7-13) give background information on the use of the flowchart.
    “The simple idea behind the ITE flowchart is that for land uses with lots of studies and a high correlation of the data to the fitted curve equation (R-squared value), it makes sense to use the equation. For uses with fewer studies or poor correlation, the rate is used. Where little or no ITE data is available, ITE suggests counting a similar local site.
    “My opinion is that If you follow the ITE flow chart for the particular land use that your project involves, you will have the backing of a majority of “progressive” agencies across the country. Moreover you will have a position that is very presentable and defendable in a hostile public meeting situation.”

  • Hi, I need some help.
    I hope this is a simple question;
    In a re-zone application, the proponent is showing a table that sais that more dwelling unit will reduce the Peak Hour Trip Ends (AM as well as PM).
    The original plan of 87 dweling unit will generate 93 Peak Hour Trips Ends but
    In a quadruplex with 100 dweling unit will generate 60 PHTE. He mentioned that the having more houses in the same lot will in fact produce less trip generation.
    This doesnt look right to me, I think that more people = more cars therefore more PHTE = more trafic.
    Is that posible that more houses in the exact same area (quadruplex Vs Single Family Homes) will in fact reduce the Peak Hour trip Ends?
    Thank for your help.

  • Octavio,
    Single family homes on average generate about 5 vehicles entering than exiting per day (10 trips) while apartments and condos generate about three vehicles entering and exiting (6 trips). This difference is largely due to driving teenagers and families with kid activities in single family homes. Studio or one bedroom apartments with one resident (one car) are also a factor compared to most single family homes that have two adults and two cars.

  • Any studies that you’re aware of that convert or relate Trip Gen manual rates into trip purpose? For a fictitious example: apartment complex generates 80 peak hour trips. 60 of them HBW, 10 HBNW, and 10 HBSchool.

  • I’m not aware of any studies that convert or relate Trip Gen manual rates into trip purpose.

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    Mike Spack

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