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• 1. [Article] Understanding Transportation in Urban China - Local Residents vs Migrant Workers

  With rapid urbanization in China and other developing economies around the world, it has become imperative to understand household transportation behavior and expenditures in these urban areas. The objective ...

  Citation × Citation Citation Abstract Copy Title: Understanding Transportation in Urban China - Local Residents vs Migrant Workers Author: Liu, Jenny H. Year: 2016 With rapid urbanization in China and other developing economies around the world, it has become imperative to understand household transportation behavior and expenditures in these urban areas. The objective of this study is to examine the differences in the determinants of household transportation expenditures within two very distinct populations in Chinese cities: local residents and migrant workers. In order to craft policies or strategies promoting sustainable transportation or livability, it is essential to understand whether the drivers that push the migrant population towards spending more on transportation or owning bikes or motorbikes are similar to drivers for the rest of the population. This is further complicated by the differential treatment of households within China’s hukou (household registration) system which determines eligibility to receive public benefits in housing or education. Because nearly 40% of the population in urban areas are migrants, it is particularly important to examine how the transportation choices and behavior of migrant households may diverge (or not) from the rest of the urban dwellers. Utilizing a unique dataset that surveys both types of households, we utilize descriptive statistics and regression models to analyze their transportation expenditures. We find that household income level and automobile ownership are the strongest predictors of household transportation expenditures. In addition, larger local resident households who are younger tend to spend more on transportation while migrant households generally spend less on transportation, particularly those with stronger social networks and those who do not hold urban hukou status. We conclude that significant differences do exist and may be exacerbated by inequitable access to public services, housing opportunities and other urban amenities in addition to major differences in household composition, preferences and levels of participation in the urban economic and social systems. Title: Understanding Transportation in Urban China - Local Residents vs Migrant Workers Author: Liu, Jenny H. Year: 2016 With rapid urbanization in China and other developing economies around the world, it has become imperative to understand household transportation behavior and expenditures in these urban areas. The objective of this study is to examine the differences in the determinants of household transportation expenditures within two very distinct populations in Chinese cities: local residents and migrant workers. In order to craft policies or strategies promoting sustainable transportation or livability, it is essential to understand whether the drivers that push the migrant population towards spending more on transportation or owning bikes or motorbikes are similar to drivers for the rest of the population. This is further complicated by the differential treatment of households within China’s hukou (household registration) system which determines eligibility to receive public benefits in housing or education. Because nearly 40% of the population in urban areas are migrants, it is particularly important to examine how the transportation choices and behavior of migrant households may diverge (or not) from the rest of the urban dwellers. Utilizing a unique dataset that surveys both types of households, we utilize descriptive statistics and regression models to analyze their transportation expenditures. We find that household income level and automobile ownership are the strongest predictors of household transportation expenditures. In addition, larger local resident households who are younger tend to spend more on transportation while migrant households generally spend less on transportation, particularly those with stronger social networks and those who do not hold urban hukou status. We conclude that significant differences do exist and may be exacerbated by inequitable access to public services, housing opportunities and other urban amenities in addition to major differences in household composition, preferences and levels of participation in the urban economic and social systems. Close

• 2. [Article] The Trade-offs between Population Density and Households' Transportation-housing Costs

  As metropolitan area governments and others promote density-promoting “smart growth” policies, finer analysis is needed to quantify the impact of such policies on households' transportation and housing ...

  Citation × Citation Citation Abstract Copy Title: The Trade-offs between Population Density and Households' Transportation-housing Costs Author: Wang, Haizhong Year: 2015 As metropolitan area governments and others promote density-promoting “smart growth” policies, finer analysis is needed to quantify the impact of such policies on households' transportation and housing costs. Existing research suggests that households in urban areas trade-off between housing costs and transportation costs, but does not explore how policies to increase urban densities might explicitly impact this balance. Furthermore, the research does not adequately distinguish between the effect of urban area density and the effects of other factors associated with urban area density (e.g metropolitan area size and household incomes) on housing costs. This research uses the 2000 Census Public Use Micro Sample (PUMS) person and household data from 23 of the nation's most densely populated states to identify the impact of increased population density on three housing cost measures: household rents, housing unit values, and monthly mortgage payments. Log linear models were estimated for each housing cost measure using least-squares regression. Dependent variables included household, housing unit, and geographic area characteristics, including population density. The models were found to be very similar to one another in terms of the statistical significance and values of estimated model parameters. Population density (measured at the PUMS area level) was found to be statistically significant at the 0.01 level for all housing cost measures. Although significant, the parameter estimates show that the elasticity of housing cost with respect to population density is low, ranging from 0.041 to 0.05. This research also explores the relationship between housing costs and accessibility. Results show that households living in areas closer to jobs (as indicated by shorter average commute times) and households utilizing fixed route transit systems have marginally higher housing costs. Title: The Trade-offs between Population Density and Households' Transportation-housing Costs Author: Wang, Haizhong Year: 2015 As metropolitan area governments and others promote density-promoting “smart growth” policies, finer analysis is needed to quantify the impact of such policies on households' transportation and housing costs. Existing research suggests that households in urban areas trade-off between housing costs and transportation costs, but does not explore how policies to increase urban densities might explicitly impact this balance. Furthermore, the research does not adequately distinguish between the effect of urban area density and the effects of other factors associated with urban area density (e.g metropolitan area size and household incomes) on housing costs. This research uses the 2000 Census Public Use Micro Sample (PUMS) person and household data from 23 of the nation's most densely populated states to identify the impact of increased population density on three housing cost measures: household rents, housing unit values, and monthly mortgage payments. Log linear models were estimated for each housing cost measure using least-squares regression. Dependent variables included household, housing unit, and geographic area characteristics, including population density. The models were found to be very similar to one another in terms of the statistical significance and values of estimated model parameters. Population density (measured at the PUMS area level) was found to be statistically significant at the 0.01 level for all housing cost measures. Although significant, the parameter estimates show that the elasticity of housing cost with respect to population density is low, ranging from 0.041 to 0.05. This research also explores the relationship between housing costs and accessibility. Results show that households living in areas closer to jobs (as indicated by shorter average commute times) and households utilizing fixed route transit systems have marginally higher housing costs. Close

• 3. [Article] Edged Out: Location Efficient Housing and Low Income Households in the Portland Region

  Transportation costs are typically a household’s second largest expense after housing. Low income households are especially burdened by transportation costs, with low income households spending up to two ...

  Citation × Citation Citation Abstract Copy Title: Edged Out: Location Efficient Housing and Low Income Households in the Portland Region Author: Tremoulet, Andrée, Dann, Ryan Year: 2016 Transportation costs are typically a household’s second largest expense after housing. Low income households are especially burdened by transportation costs, with low income households spending up to two times as much of their income on transportation than higher income households (Litman, 2013). Thus, access to location efficient housing is especially important to low income households, including those who use a housing voucher to help pay for housing costs. This seminar presents the results of a two-year project supported by the Portland region's four public housing authorities to design and test tools to help people with housing vouchers find location efficient housing. We examine the challenges that residents faced and discuss policy implications. Title: Edged Out: Location Efficient Housing and Low Income Households in the Portland Region Author: Tremoulet, Andrée, Dann, Ryan Year: 2016 Transportation costs are typically a household’s second largest expense after housing. Low income households are especially burdened by transportation costs, with low income households spending up to two times as much of their income on transportation than higher income households (Litman, 2013). Thus, access to location efficient housing is especially important to low income households, including those who use a housing voucher to help pay for housing costs. This seminar presents the results of a two-year project supported by the Portland region's four public housing authorities to design and test tools to help people with housing vouchers find location efficient housing. We examine the challenges that residents faced and discuss policy implications. Close

• 4. [Article] The Importance of Housing, Accessibility, and Transport Characteristic Ratings on Stated Neighborhood Preference

  Travel demand models commonly lack the ability to understand how changing residential preferences influence future housing, land use, and transportation policies. As communities struggle to address social ...

  Citation × Citation Citation Abstract Copy Title: The Importance of Housing, Accessibility, and Transport Characteristic Ratings on Stated Neighborhood Preference Author: Currans, Kristina Marie Year: 2016 Travel demand models commonly lack the ability to understand how changing residential preferences influence future housing, land use, and transportation policies. As communities struggle to address social challenges related to increased economic uncertainty, transportation and land use planning have become increasingly centered on assumptions concerning the market for residential environments and travel choices. In response, an added importance has been placed on the development of toolkits capable of providing robust and flexible models to aid in understanding how differing assumptions contribute to a set of planning scenarios and how future residential location decisions may be made. In this study, we aim to examine the ability for current land use and transportation models to adequately account for the mechanism that drive households to prefer different neighborhoods based on typical transportation modeling methods. In particular, we conduct an original stated preference survey to identify the characteristics and preferences of individuals and households that influence unconstrained residential neighborhood preferences. Our objectives are to (a) determine the key drivers of residential neighborhood preferences, (b) test the contribution of sociodemographic and economic household characteristics commonly used in regional modeling tools to allocate households regionally across neighborhoods (e.g. household size, income, age, tenure), and (c) identify the preference profiles that can improve the sensitivity of our regional and statewide transportation-land use models to residential neighborhood preferences. The presentation for this seminar was done jointly with Steven Gehrke. It can be accessed at http://archives.pdx.edu/ds/psu/18234. Title: The Importance of Housing, Accessibility, and Transport Characteristic Ratings on Stated Neighborhood Preference Author: Currans, Kristina Marie Year: 2016 Travel demand models commonly lack the ability to understand how changing residential preferences influence future housing, land use, and transportation policies. As communities struggle to address social challenges related to increased economic uncertainty, transportation and land use planning have become increasingly centered on assumptions concerning the market for residential environments and travel choices. In response, an added importance has been placed on the development of toolkits capable of providing robust and flexible models to aid in understanding how differing assumptions contribute to a set of planning scenarios and how future residential location decisions may be made. In this study, we aim to examine the ability for current land use and transportation models to adequately account for the mechanism that drive households to prefer different neighborhoods based on typical transportation modeling methods. In particular, we conduct an original stated preference survey to identify the characteristics and preferences of individuals and households that influence unconstrained residential neighborhood preferences. Our objectives are to (a) determine the key drivers of residential neighborhood preferences, (b) test the contribution of sociodemographic and economic household characteristics commonly used in regional modeling tools to allocate households regionally across neighborhoods (e.g. household size, income, age, tenure), and (c) identify the preference profiles that can improve the sensitivity of our regional and statewide transportation-land use models to residential neighborhood preferences. The presentation for this seminar was done jointly with Steven Gehrke. It can be accessed at http://archives.pdx.edu/ds/psu/18234. Close

• 5. [Article] How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas?

  Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. ...

  Citation × Citation Citation Abstract Copy Title: How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas? Author: Scheer, Brenda, Ewing, Reid, Park, Keunhyun, Khan, Shabnam Sifat Ara Year: 2017 Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. Existing travel behavior studies in the context of TOD, however, are limited in terms of small sample size, inconsistent TOD classification methods, and failure to control for residential self-selection. Thus, this study has three research questions. First, how can we distinguish between Transit-oriented development (TOD) and Transit-adjacent development (TAD)? Second, how do travel behaviors vary between TODs and TADs? Third, how does transportation affordability vary between TODs and TADs? This study utilizes cluster analysis to classify station area types and propensity score matching to control residential self-selection. From cluster analysis with built-environment factors—density, diversity, and walkability—in a half-mile buffer, this study classifies existing station areas as TOD, TAD or Hybrid types. After controlling for residential self-selection, it shows that a TOD motivates its residents to walk more and take transit more while using personal vehicles less. The significant difference between TOD and TAD in both VMT and the number of auto trips demonstrates that TODs make the personal vehicle trips shorter and fewer. Travel behavior in the Hybrid type demonstrates the possibility of gradual and practical change. Finally, the percentage of household income spent on transportation is lower in TOD households than TAD households. This shows that a TOD household is likely to save enough money on vehicle ownership and use that, while it likely spends more on transit, the final result is a significantly lower financial burden from transportation. Title: How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas? Author: Scheer, Brenda, Ewing, Reid, Park, Keunhyun, Khan, Shabnam Sifat Ara Year: 2017 Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. Existing travel behavior studies in the context of TOD, however, are limited in terms of small sample size, inconsistent TOD classification methods, and failure to control for residential self-selection. Thus, this study has three research questions. First, how can we distinguish between Transit-oriented development (TOD) and Transit-adjacent development (TAD)? Second, how do travel behaviors vary between TODs and TADs? Third, how does transportation affordability vary between TODs and TADs? This study utilizes cluster analysis to classify station area types and propensity score matching to control residential self-selection. From cluster analysis with built-environment factors—density, diversity, and walkability—in a half-mile buffer, this study classifies existing station areas as TOD, TAD or Hybrid types. After controlling for residential self-selection, it shows that a TOD motivates its residents to walk more and take transit more while using personal vehicles less. The significant difference between TOD and TAD in both VMT and the number of auto trips demonstrates that TODs make the personal vehicle trips shorter and fewer. Travel behavior in the Hybrid type demonstrates the possibility of gradual and practical change. Finally, the percentage of household income spent on transportation is lower in TOD households than TAD households. This shows that a TOD household is likely to save enough money on vehicle ownership and use that, while it likely spends more on transit, the final result is a significantly lower financial burden from transportation. Close

• 6. [Article] When Cities Shrink, Affordability Does Too

  To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research ...

  Citation × Citation Citation Abstract Copy Title: When Cities Shrink, Affordability Does Too Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research literature and in the LAI regarding household expenditures and transportation accessibility hold true when analyzing shrinking cities—generally, cities characterized by a long-term loss in occupied housing units. The project was led by Joanna Ganning of Cleveland State University, who has conducted previous research into shrinking cities with the support of the NITC program. Title: When Cities Shrink, Affordability Does Too Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research literature and in the LAI regarding household expenditures and transportation accessibility hold true when analyzing shrinking cities—generally, cities characterized by a long-term loss in occupied housing units. The project was led by Joanna Ganning of Cleveland State University, who has conducted previous research into shrinking cities with the support of the NITC program. Close

• 7. [Article] What Do We Know About Location Affordability in U.S. Shrinking Cities?

  In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing ...

  Citation × Citation Citation Abstract Copy Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Close

• 8. [Article] Do TODs Make a Difference?

  In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based ...

  Citation × Citation Citation Abstract Copy Title: Do TODs Make a Difference? Author: Nelson, Arthur C., Miller, Matt, Eskic, Dejan, Kim, Keuntae, Ewing, Reid, Liu, Jenny H., Berggren, Matt, Mumuni, Zakari Year: 2015 In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based on key demographic characteristics; (3) housing affordability based on transportation costs; and (4) job-worker balance as a measure of accessibility. Prior literature has not systematically evaluated TOD outcomes in these respects with respect to light rail transit (LRT), commuter rail transit (CRT), bus rapid transit (BRT), and streetcar transit (SCT) systems. Our analysis helps close some of these gaps. We apply our analysis to 23 fixed-guideway transit systems operating in 17 metropolitan areas in the South and West that have one or more of those systems. We find: (1) Most TOD areas gained jobs in the office, knowledge, education, health care and entertainment sectors, adding more than $100 billion in wages capitalized over time; (2) In assessing economic resilience associated with LRT systems, jobs continued to shift away from TOD areas before the Great Recession, the pace slowed during the recession but reversed during recovery, leading us to speculate that LRT TOD areas may have transformed metropolitan economies served by LRT systems; (3) Rents for offices, retail stores and apartments were higher when closer to SCT systems, had mixed results with respect LRT systems, but were mostly lower with respect to CRT systems (our BRT sample was too small to evaluate); (4) SCT systems performed best in terms of increasing their TOD-area shares of metropolitan population, households and householders by age, housing units, and renters with BRT systems performing less well while LRT and CRT systems experienced a much smaller shift in the share of growth; (5) Household transportation costs as a share of budgets increase with respect to distance from LRT transit stations to seven miles, suggesting the proximity to LRT stations reduces total household transportation costs; (6) Emerging trends that may favor higher-wage jobs locating in TOD areas over time than lower- or middle-wage jobs, perhaps because TOD areas attract more investment which requires more productive, higher-paid labor to justify the investment; and (7) The share of workers who commute 10 minutes or less to work increases nearly one-half of 1 percent for each half-mile their resident block group is to an LRT transit station, capping at a gain of 1.3 percent, which is not a trivial gain. Our report summarizes case studies of 23 transit systems and three journal articles based on our research. Title: Do TODs Make a Difference? Author: Nelson, Arthur C., Miller, Matt, Eskic, Dejan, Kim, Keuntae, Ewing, Reid, Liu, Jenny H., Berggren, Matt, Mumuni, Zakari Year: 2015 In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based on key demographic characteristics; (3) housing affordability based on transportation costs; and (4) job-worker balance as a measure of accessibility. Prior literature has not systematically evaluated TOD outcomes in these respects with respect to light rail transit (LRT), commuter rail transit (CRT), bus rapid transit (BRT), and streetcar transit (SCT) systems. Our analysis helps close some of these gaps. We apply our analysis to 23 fixed-guideway transit systems operating in 17 metropolitan areas in the South and West that have one or more of those systems. We find: (1) Most TOD areas gained jobs in the office, knowledge, education, health care and entertainment sectors, adding more than $100 billion in wages capitalized over time; (2) In assessing economic resilience associated with LRT systems, jobs continued to shift away from TOD areas before the Great Recession, the pace slowed during the recession but reversed during recovery, leading us to speculate that LRT TOD areas may have transformed metropolitan economies served by LRT systems; (3) Rents for offices, retail stores and apartments were higher when closer to SCT systems, had mixed results with respect LRT systems, but were mostly lower with respect to CRT systems (our BRT sample was too small to evaluate); (4) SCT systems performed best in terms of increasing their TOD-area shares of metropolitan population, households and householders by age, housing units, and renters with BRT systems performing less well while LRT and CRT systems experienced a much smaller shift in the share of growth; (5) Household transportation costs as a share of budgets increase with respect to distance from LRT transit stations to seven miles, suggesting the proximity to LRT stations reduces total household transportation costs; (6) Emerging trends that may favor higher-wage jobs locating in TOD areas over time than lower- or middle-wage jobs, perhaps because TOD areas attract more investment which requires more productive, higher-paid labor to justify the investment; and (7) The share of workers who commute 10 minutes or less to work increases nearly one-half of 1 percent for each half-mile their resident block group is to an LRT transit station, capping at a gain of 1.3 percent, which is not a trivial gain. Our report summarizes case studies of 23 transit systems and three journal articles based on our research. Close

• 9. [Article] Multiday GPS Travel Behavior Data for Travel Analysis: The Effect of Day-to-Day Travel Time Variability on Auto Travel Choices

  This project explored the potential of archived multi-day GPS data to expand the understanding of travel-time reliability. While reliability is often observed and considered at the system or segment level, ...

  Citation × Citation Citation Abstract Copy Title: Multiday GPS Travel Behavior Data for Travel Analysis: The Effect of Day-to-Day Travel Time Variability on Auto Travel Choices Author: Dill, Jennifer, Broach, Joseph Paul, Deutsch-Burgne, Kate, Xu, Yanzhi, Guensler, Randall, Levinson, David, Tang, Wenyun Year: 2014 This project explored the potential of archived multi-day GPS data to expand the understanding of travel-time reliability. While reliability is often observed and considered at the system or segment level, travel-time uncertainty is also experienced at the household and trip level. Any move toward incorporating reliability into regional travel models will necessitate a re-examination of travel-time variation at more disaggregate levels. The analysis uses multiday vehicle-based GPS data analyzed within the Transportation Secure Data Center (TSDC). There were three major goals for the research. The first goal was to consider the ways in which multiday GPS data could be translated into data on reliability. The second goal was to explore relationships between trip- and household-level travel-time reliability and related trip, household, network, and urban location factors. The third goal involved use of the topic of reliability as a case study to test the usefulness of the TSDC in its current form for academic research. Title: Multiday GPS Travel Behavior Data for Travel Analysis: The Effect of Day-to-Day Travel Time Variability on Auto Travel Choices Author: Dill, Jennifer, Broach, Joseph Paul, Deutsch-Burgne, Kate, Xu, Yanzhi, Guensler, Randall, Levinson, David, Tang, Wenyun Year: 2014 This project explored the potential of archived multi-day GPS data to expand the understanding of travel-time reliability. While reliability is often observed and considered at the system or segment level, travel-time uncertainty is also experienced at the household and trip level. Any move toward incorporating reliability into regional travel models will necessitate a re-examination of travel-time variation at more disaggregate levels. The analysis uses multiday vehicle-based GPS data analyzed within the Transportation Secure Data Center (TSDC). There were three major goals for the research. The first goal was to consider the ways in which multiday GPS data could be translated into data on reliability. The second goal was to explore relationships between trip- and household-level travel-time reliability and related trip, household, network, and urban location factors. The third goal involved use of the topic of reliability as a case study to test the usefulness of the TSDC in its current form for academic research. Close

• 10. [Article] The Geography of the Commute

  It is a common misperception that low-income populations are transit-dependent or typically do without a car because it is too expensive. While much larger proportions of low-income populations use a mode ...

  Citation × Citation Citation Abstract Copy Title: The Geography of the Commute Author: Howland, Steven, Morris, Randy Year: 2017 It is a common misperception that low-income populations are transit-dependent or typically do without a car because it is too expensive. While much larger proportions of low-income populations use a mode of transportation other than a personal automobile to commute to work, a majority of them still use a personal automobile. In this edition of the Periodic Atlas, we looked at commuting as it relates to people of color and low-wage workers using the most recent reliable Census data as well as data from the Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LEHD-LODES). Title: The Geography of the Commute Author: Howland, Steven, Morris, Randy Year: 2017 It is a common misperception that low-income populations are transit-dependent or typically do without a car because it is too expensive. While much larger proportions of low-income populations use a mode of transportation other than a personal automobile to commute to work, a majority of them still use a personal automobile. In this edition of the Periodic Atlas, we looked at commuting as it relates to people of color and low-wage workers using the most recent reliable Census data as well as data from the Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LEHD-LODES). Close