Irvine PA12 Project: Part I: Task 2

Task 2: Site-oriented Trip Generation

Inaccurate trip generation forecasts can invalidate a traffic impact study from the start. Care must be taken to ensure that the trip-end values used are appropriate for the site being developed. The standard approach to trip generation is the use of ITE's published trip generation tables which are based on statistical analysis (regression) of local trip-generation studies performed nationwide. The generality of the studies included in the analysis can introduce errors into trip generation calculations. The following concerns are particularly relevant for the current project:

• location variation: Travel patterns in Southern California tend to be fairly unique and do not always correspond to data from other parts of the country.
• passer-by traffic: Certain development types (e.g., fast food restaurants) tend to attract people who are already making trips in the area causing them to add an additional stop to their current trip. This trip chaining behavior can cause over estimates of new trip generation caused by the site which must be accounted for.
• mixed-use development: As with passer-by traffic, mixed-use development tends to encourage trip chaining behavior. For example, a restaurant in a development which also contains office space will likely see some of its attractions coming from the adjoining office instead of generating trips from non-site locations.

1. Survey general characteristics of site

   At a minimum, this should include:
   1. Location type (shopping center, office park, etc.)
   2. A description of the mix of land-uses. Assess and summarize each unit in the development. Classify them by use and give a rough estimate of the independent variable(s) which you predict will be correlated to trip-end generation by the unit (see Table 2.1 for examples).
   3. Describe site connection to the adjacent streets. At a minimum, this assessment should include:
      1. Number of driveways with detail of which approaches they provide access.
      2. Classification of connecting streets (e.g., arterial, collector, etc.) and general characteristics (speed, number of lanes, etc.).
      3. Adjacent intersection characteristics
   4. Parking characteristics
      1. Total number of spaces
      2. Parking costs (if any)
   Summarize this information using part 1 of ITE's Trip Generation Data Form and provide a site sketch.
   Table 2.1: Typical independent variables by land-use

   Land use		independent variable
   Office		gross floor area, # of employees
   Commercial		gross leasable area, # of employees
   Restaurant		gross leasable area, # of employees
   Hotel		# of rooms, # of employees
   Bank		gross area, # of employees, # of drive-in windows
   Health club/recreational		gross area

2. Determine peak-hour driveway volumes

   During the assigned hour for the site, count trip demand at the site. Include:

   1. Total volume entering all driveways (count trucks separately)
   2. Total volume exiting all driveways (count trucks separately)
   3. Note the number of persons in each vehicle (when possible).
   Use part 2 of ITE's Trip Generation Data Form to report the data:

3. Submit driveway count data

   Submit data at the beginning of the discussion session on Friday, May 1st. No formal report is required. The data will be returned to you for the remaining subtasks.

4. Estimate trip generation for the site

   Estimate the expected trip generation rate for the site:

   1. By summing trip generation determined from ITE average trip rates for each land use at the site.

      Using the site land-use summary in Table 2.2, calculate the vehicle trip-ends for each land use type at the site for the PM peak period using the ITE methodology and tables provided. Calculate the total trip-ends for the PM peak by summing the individual use trip ends.

      Use the following assumptions in your calculations:

      • There is no transit usage.
      • Trip purposes for all land uses are split:
        HBW=5%, HBO=49%, NHB=46%.
      • Occupancies by land use type and trip purpose are as given in Table 2.3

        
        
        

        Table 2.3: Trip splits by purpose

        Land use	HBW		HBO		NHB
        Supermarket	1.1		1.40		1.40
        Clinic	1.1		1.15		1.15
        Retail-specialty	1.1		1.30		1.10
        Restaurant-Fast food	1.1		1.40		1.20
        Resaurant-Quality	1.1		1.50		1.30

        Note: When the ITE trip generation data has no information on vehicle occupancy, assume no adjustment is required.

   2. using ITE shopping center (LU 820) average trip rate and trip rate equation

      Use the following assumptions in your calculations:

      • There is no transit usage.
      • Trip purposes for all land uses are split:
        HBW=5%, HBO=49%, NHB=46%.
      • Occupancies by trip purpose are:
        HBW=1.1, HBO=1.25, NHB=1.15.

   3. using ITAM model trip generation methodology.

      The ITAM model determines total daily person trip ends for this zone based on the following equation:

      Ln T = 0.625 Ln X + 6.376

      Where:

      • T is the daily trip ends for the site
      • X is the total occupied space in thousands of square feet.

      Determine the total daily person trip ends using this equation and convert to PM peak vehicle trip ends using the following assumptions:

      • There is no transit usage.
      • The PM peak proportion of the total is 7.2%.
      • Trip purposes for all land uses are split:
        HBW=5%, HBO=49%, NHB=46%.
      • Occupancies by trip purpose are:
        HBW=1.1, HBO=1.25, NHB=1.15.

   Note: Trip generation calculations are driven by the assumptions underlying them. Therefore, you must state all assumptions with justifications for them and show all non-trivial calculations in performing this analysis.

   
   

5. Compare trip generation methodologies to observed data

   A summary of the driveway counts collected during subtasks 2.1-2.3 is given in Table 2.4. Use this data to compare the observed PM peak vehicle trip ends (use the average for Tuesday and Wednesday) to the three trip generation methodologies used in subtask 2.4. Questions to consider include:

   • Do the observed counts compare to each methodology as you would expect?
   • Estimate the capture rate for this site due to multiple land use effects. Were their fewer trip-ends observed than predicted by the methodology in sub task 2.4.1? If so, what percent of trips were captured by the multiple land uses?
   • Do these results make sense? If not, what factors do you think may account for any discrepancies?

6. Prepare a DRAFT Task 2 Report

   Prepare a DRAFT Task 2 Report documenting this work. Follow all Project Guidelines in the preparation of this report. Submit this report by May 8, 1998.