Trip Generation Rates for Transportation Impact Analyses of Infill Developments (2013) / Chapter Skim
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17 Chapter 3 summarized the process the research team employed to select the approach used as the basis for developing the estimation methods described in this chapter. The following sections present two proposed methods, both of which are based on the selected approach -- baseline ITE rate adjustment based on empirical data.
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18 4.2 Proposed Methodology This report proposes an approach of adjusting ITE trip generation data (rates or trips) using a single computational procedure that employs baseline and infill adjustment factors consisting of (a)
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19 the research team chose to present a flexible and adaptable system for classifying context. The primary requirement of the system is consistency in its application, especially when comparing potential proxy sites with the proposed project being studied by the practitioner.
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20 transportation serving the subject area. Contexts that qualify for infill development are served by rail or high-frequency bus transit (12)
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21 large proportion of a metropolitan area's land being built up (covered with buildings and infrastructure) relative to the total land area.
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22 an automobile mode share in infill areas. Step 3 converts the baseline ITE person-trip estimates to infill person-vehicle trips using Equation #2: Person-Vehicle-Trips Person-Trips 100% %Transit %WalkBicycle INFILL BASELINE INFILL INFILL ]
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23 bicycle trips, and a low vehicle occupancy (a range of 1.02 to 1.05 persons/vehicle) , is recommended for use.
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24 planning horizons. Planning horizons can range from the current year to 20 years or more in the future, or whatever period of time the proposed project would take to fully build out.
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25 The minimum required data for estimating infill trip generation adjustments are listed in Table 4.1, which describes the required variables and how they are used in deriving the adjustment factors. These variables are generally standard in travel surveys and should be available, in one form or another, from all the major metropolitan areas.
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26 Residential trip records do not record delivery, services, or guest trips unless recorded by another participant. This should not significantly affect the derivation of mode split or vehicle occupancy of residential uses.
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27 (used in travel demand forecasting) was used to determine employment density.
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28 4.7.5 Extracting Mode-Share Adjustment Factors Extracting the adjustment factors from a linked-trip database involves the following major activities: • Begin with a linked-trip database of all daily travel in which each record contains a trip that has at least one trip end originating in or destined to a TAZ that meets context criteria. • Use the activity purpose at trip origins and destinations to extract records with activities that represent the four proposed study land uses (residential, restaurant, retail, and office)
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29 corridors that meet transit proximity criteria, and extract records that have at least one trip end within these zones. • Separate weekday from weekend trip records.
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