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25 Table 29. URBEMIS2002 trip reduction credits that income levels and vehicle ownership affect the magni- related to internal trip capture factors. tude of a person's and household's travel. Travel time, travel distance, available travel modes, residential development Land Use Type Physical Measures density, and other factors have all been shown to influence Residential Non-Residential travel characteristics. Table 30 lists a wide range of variables Net residential density Up to 55% Not applicable that could influence internal trip capture. Also listed are con- Mix of uses Up to 9% Up to 9% siderations that are applicable in selecting a smaller set of Local-serving retail 2% 2% variables for consideration in developing an improved esti- Transit service Up to 15% Up to 15% mation procedure. Table 30 also lists (in the first column) the final candidate Pedestrian/bicycle friendliness Up to 9% Up to 9% variables selected by the research team for consideration in Total Up to 90% Up to 90% developing an improved estimation method. These variables Source: (51, p. 3) were selected based on causal relationship to internal trip cap- ture, ease of quantification in the field and from preliminary modeling is an enhancement to standard modeling that may site plans, potential data availability, data collection complex- address internal capture rates more effectively. ity, and likelihood of acceptance by the user community. Chap- Some have tried to adapt the ULI shared parking method ter 3 addresses these variables more fully. for use in estimating trip generations for MXDs. While the Trends in MXD and classification of land uses found in ULI shared parking method is applicable to MXDs, it is valid MXDs are covered in Appendixes A and B. only for estimating parking accumulation and not for trip generation estimation (54); however, it is apparent that some Summary preparers are using it to estimate internal trip capture. These findings revealed several estimation techniques and a lot of related data and research findings, but detailed sur- Trip Capture Variables veys of only seven MXDs (six in two Florida studies and one Travel is affected by a myriad of factors ranging from trav- in Virginia). Hard-copy survey data were acquired for the six elers' own demographic characteristics to characteristics of Florida sites. All were completed by the mid-1990s, prior to the trip destination. Extensive research has been conducted the time that ITE published the first edition of its Trip Gener- related to travel behavior. For example, it is widely accepted ation Handbook in 1999 (55), which as an ITErecommended Table 30. Candidate independent variables. Anticipated Use Variable Sensitivity Comments No Density/compactness High Proximity High Combine as a single independent variable (proximity) No Connectivity High Reflect instead in mode of access that may be considered similar in effect. Parking-supply constraints reduce total trip generation but may not significantly change internal trip No Parking Moderate capture percentage. Normally only a factor in central business districts (CBDs), TODs; such sites may require special study anyway. Add parking garage "access time" to impedance used for "competing external opportunity" model component. Land use synergy High Use as "yes/no" variable to match users among site land uses Balance of land use High Use as control check quantities Principal trip purpose No High Covered largely by land uses and time of day to site Driver trips can be associated with mode of access to site for primary trip. Primary trip purpose strongly influences mode of Mode of access Moderate access. Will be a significant factor where good transit service exists. Time-of-day Moderate Provide one trip capture table for each time period of interest (e.g., weekday A.M. peak hour, P.M. peak hour, midday; Day of week, season Moderate Saturday peak hour) Competing external Attempt to quantify if data can be found. Data expensive to No High opportunities collect.