The purpose of this chapter is to discuss the urban-context adjustment framework proposed in this thesis, including: an overview of how the developed adjustments are applied to establishment-level data collected in accordance with ITE’s Trip Generation Handbook, the process of development for the adjustment methods, and an overview of the how the data were organized and applied. The objective of this research is to develop and test an urban-context adjustment methodology to use as a widely-available, ready-to-use adjustment methodology for ITE’s Trip Generation Handbook vehicle trip generation estimates. This methodology must be applicable to establishments looking to develop in non-suburban areas with low to high activity densities (population and employment) located within a metropolitan planning organization (MPO). Additionally, relevant development locations may or may not be near rail or high-quality transit areas, and therefore, must be sensitive to differences in transit quality. Finally, this methodology must consider the limited data availability for most regions of the United States, and should not require jurisdictions to collect substantial amounts of additional data in order to apply this adjustment.
Recalling Figure 2 from the Introduction (repeated below), there are five steps to applying a mode share adjustment to ITE’s Trip Generation Handbook estimates for any given urban development.
Figure 2. Urban-Context Mode Share Adjustment: Applied to ITE's Trip Generation Handbook Vehicle Trip Estimates
In Step II, the analyst converts ITE vehicle trip estimates to a person trip estimate, and then in Step IV., they allocate the estimated person trips into different modes based on the urban context mode share and vehicle occupancy estimated in Step III. Equation 2 and Equation 3, below, describe mathematically the process of conversion between vehicle trips to person trips and back to vehicle trips discussed in Steps II. and IV.
Although Section 3.3 describes three different methods for estimating the urban-sensitive automobile mode share, the framework for applying any of these three mode-share adjustments remains the same as shown in Equation 2 and Equation 3.
Step I.
Calculate the ITE’s Trip Generation Handbook vehicle trip generation estimate for the development.
Step II.
Apply the estimated automobile mode share and vehicle occupancy for ITE’s suburban vehicle trip generation rates to the vehicle trip estimates from (I.) to
calculate the assumed total ITE person trips for that development.
Step III.
Estimate the automobile mode share and vehicle occupancy for the infill development location and urban area-type using the methodologies developed in this
thesis.
Step IV.
Use the estimated mode shares and vehicle occupancy rates from (III) to allocate the total estimated person trips for that location (II) into travel modes.
Step V.
Apply the new vehicle trip estimates for the development, now adjusted for its urban context (IV.), in traffic impact analysis.
Equation 2. Converting an ITE Vehicle Trip End Estimate into an ITE Person Trip End Estimate
Equation 3. Converting an ITE Person Trip End Estimate into an Urban Context Adjusted (UCA) Vehicle Trip End Estimate
Where,
This is the outcome of the adjustment, a vehicle trip end estimate adjusted for urban context [vehicle trip ends per independent variable per time period studied].
Urban context adjustment automobile mode share as a percent of total person trip ends, estimated using a HTS UCA methodology described within this section.
Urban context adjustment vehicle occupancy rate as a percent of total person trip ends, estimated using a HTS UCA methodology described within this section.
ITE’s Trip Generation Handbook Estimated Person Trip Ends, from ITE’s Trip Generation Handbook vehicle trip end estimates [person trip ends per independent variable per time period studied].
ITE’s Trip Generation Handbook vehicle trip end estimations [vehicle trip ends per independent variable per time period studied].
ITE automobile mode share as a percent of total person trip ends, provided within the ITE’s Trip Generation Handbook and representative of a suburban “base case” land use. If no values are available, assume a 100%
automobile mode share.
ITE vehicle occupancy rate as a percent of total person trip ends, provided with the ITE’s Trip Generation Handbook and representative of a suburban “base case” land use. If no values are available, assume a rate of one person per vehicle.
Step I. is covered in detail in ITE’s Trip Generation Handbook and will not be discussed in this thesis. The assumptions used in this proposed mode share adjustment are discussed further in Section 3.1. Following the diagram discussed in the introduction, and repeated below in Figure 3, the HTS data compiled and organized to provide observations of individual-level travel at a wide range of urban contexts is discussed Section 3.2.1; the built environment data used to define the urban context is discussed in Section 3.2.2.
Utilizing both of these data sources, automobile mode share and vehicle occupancy equations are developed in Section 3.3. These equations are usable for estimating the urban context mode share adjustment proposed in Figure 2.
Figure 3. Process and Contribution of This Research
Moreover, independently collected establishment-level data were used to test for improvements in the accuracy of vehicle trip estimates compared with the original ITE’s Trip Generation Handbook estimates (Section 3.4). The results of this chapter are discussed in the following Chapter 4.0.