The National Academies Press

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Pages 91-112

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From page 91... ... 91 B.1 Demographic Sector The stock variable is the number of people in a regional population of interest, and it is segmented into dimensions. These dimensions were selected for their strong relationship with travel behavior, based on the knowledge of the research team and Tasks 1 and 2 findings, documented in the project memoranda. Read the entire page →
From page 92... ... 92 The Effects of Socio-Demographics on Future Travel Demand Running the SD model for a specific region requires the initial distribution of the population along all these variables simultaneously. With the categories above, that requires values for 6 × 4 × 3 × 4 × 2 × 3 × 3 = 5,184 different combinations, or "cells" in a multidimensional matrix. Read the entire page →
From page 93... ... Impacts 2050 Model Structure Documentation 93 • Acculturation transition: People's race/ethnicity and birthplace (foreign or native) do not change during their lifetime. Read the entire page →
From page 94... ... 94 The Effects of Socio-Demographics on Future Travel Demand Note that the results of "marriage," "divorce," or "leave nest" are not purely structural in terms of whether there will be any children in the resulting household. Singles who marry or young adults who "leave the nest" may join a partner who already has children. Read the entire page →
From page 95... ... Impacts 2050 Model Structure Documentation 95 p p (p ) q KEY FOR FLOW DIAGRAM: Rectangles are stock variables. Read the entire page →
From page 96... ... 96 The Effects of Socio-Demographics on Future Travel Demand the attractiveness of the region/area type for residents (see below for more information on this) Read the entire page →
From page 97... ... Impacts 2050 Model Structure Documentation 97 weight on housing availability and traffic congestion (especially since someone can move within the region but keep the same job) Read the entire page →
From page 98... ... 98 The Effects of Socio-Demographics on Future Travel Demand B.2 Travel Behavior Subsector The models are applied separately for every combination of socio-demographic characteristics in the model. They are applied in the following order: 1. Read the entire page →
From page 99... ... Impacts 2050 Model Structure Documentation 99 The model utility coefficients are shown, along with the related t-statistic. "Own car" has an implicit utility of 0, and separate utility functions were estimated for the other two alternatives. Read the entire page →
From page 100... ... 100 The Effects of Socio-Demographics on Future Travel Demand this effect is over and above the income effects that are simultaneously included in the model. A worker effect is also included simultaneously, and has strong negative coefficients, indicating that workers are more likely to have their "own car." The urban and rural variables also have strong, expected effects, with people living in urban areas most likely to live in low-/no-car households, and those in rural areas most likely to be in "own car" households. Read the entire page →
From page 101... ... Impacts 2050 Model Structure Documentation 101 fewer nonwork trips. All of these effects are typically found in travel demand models. Read the entire page →
From page 102... ... 102 The Effects of Socio-Demographics on Future Travel Demand We again used the same set of variables as for the preceding models. However, we did have one additional variable -- the price of gasoline. Read the entire page →
From page 103... ... Impacts 2050 Model Structure Documentation 103 to walk; this effect is even stronger for workers born outside the United States. The effects by area type are also strong, as workers in urban areas are most likely to use transit or walk/bike for their work trip, while those in rural areas are less likely to use those modes and more likely to rideshare. Read the entire page →
From page 104... ... 104 The Effects of Socio-Demographics on Future Travel Demand Again, car ownership is very important, with those in low-car and especially no-car households much more likely to choose any of the alternatives to being a car driver. It is interesting that once car ownership has been taken into account, those in high-income groups are also more likely to choose alternatives to driving. Read the entire page →
From page 105... ... Impacts 2050 Model Structure Documentation 105 Six different models get the six different inputs to the VMT equation. This is VMT per person per day. Read the entire page →
From page 106... ... 106 The Effects of Socio-Demographics on Future Travel Demand taking into consideration other variables, particularly area type. People in low-car and no-car households tend to make shorter trips by car -- perhaps because it is more difficult to find a ride to farther destinations. Read the entire page →
From page 107... ... Impacts 2050 Model Structure Documentation 107 • Urban, suburban rural developable space • Urban, suburban, rural protected space B.3.1 Land-Use Rates of Change Figure B-2 presents a flow diagram for the land-use sector. The rates of change that are relevant to this sector are: • Development of Residential Space and Release of Residential Space: Converting land from developable space to use for housing. Read the entire page →
From page 108... ... 108 The Effects of Socio-Demographics on Future Travel Demand The equations that comprise the rates for the first three bullets have four main components: (1) the existing stock of space in the use that would be converted out of; (2) Read the entire page →
From page 109... ... Impacts 2050 Model Structure Documentation 109 The equations that comprise this sector have three main components: (1) the existing stock of jobs, (2) Read the entire page →
From page 110... ... 110 The Effects of Socio-Demographics on Future Travel Demand of supply and demand for jobs, reflecting the availability of labor; (3) the balance of supply and demand for commercial space, reflecting the availability of land; and (4) Read the entire page →
From page 111... ... Impacts 2050 Model Structure Documentation 111 The demand for peak-hour road supply is a function of the number and distance of work and nonwork trips by car drivers made by people living in each area type, and depending on a number of other user inputs, including the mix of road type/area type combinations used by commuters for each type of flow (e.g., suburban–urban commutes) and the peak-hour fraction of daily trips assumed for work and nonwork trips. Read the entire page →
From page 112... ... 112 The Effects of Socio-Demographics on Future Travel Demand For addition of road and transit capacity, the main indicator is the amount of new capacity needed to meet passenger demand, if any, based on the demand calculations described above. The exogenous scenario inputs represent (1) Read the entire page →

From page 91...

... 91 B.1 Demographic Sector The stock variable is the number of people in a regional population of interest, and it is segmented into dimensions. These dimensions were selected for their strong relationship with travel behavior, based on the knowledge of the research team and Tasks 1 and 2 findings, documented in the project memoranda.