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• 1. [Article] Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods

  Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which ...

  Citation × Citation Citation Abstract Copy Title: Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods Author: Clifton, Kelly J., Gehrke, Steven R. Year: 2014 Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which contribute to regional and statewide travel demand models. These data have utility beyond travel demand modeling in their application to transportation policy and travel behavior research. As the demand on these data increase, so have the quantity of information collected. Detailed geospatial referencing of the home, work and other travel destinations are common practice and permit the integration with other spatially archived data sources, such as land use characteristics, transportation system information, and other built environment, social and economic data. Other public agencies, private consultancies, non-profits and educational institutions may benefit from access to the original data with applications to areas such public health, equity, transportation safety and urban planning. Oregon Modeling Collaborative (OMC) has entered into an agreement with Oregon Modeling Steering Committee (OMSC) to host and make available Oregon Household Activity Survey (OHAS) datasets. But wide distribution of these important and expensive data is limited by the requirement to protect the confidentiality of survey participants, who are guaranteed anonymity in exchange for participation. Data are often aggregated to a geographic level such as Census tracts or transportation analysis zones (TAZs) before disseminating to the public, which limits the utility of this information. This project aims to develop a methodology to permit dissemination of these spatially-explicit data to a wider range of public constituents while at the same time, protecting the identities of study participants. Making use of these data, this project will use geographical perturbation methods to add noise to the original data to protect confidentiality while at the same time allowing the detailed geo-spatial referencing to be included in the disseminated data. The process includes: The coordinates (locations) will be geographically perturbed (masked) so that they do not reveal the identity of the traveler while at the same time retaining spatial relevance and resolution. Here the limits of the perturbation (minimum and maximum displacement) need to be determined that a) ensure confidentiality and b) minimize the errors introduced to the data. The original and perturbed (masked) data will be compared using various statistical approaches to develop a set of confidence measures for different types of transportation applications. For example, geographically perturbed (masked) may be more robust for automobile travel measures, such as vehicle miles traveled (VMT) or transit accessibility than for detailed pedestrian or bicycle trip attributes. This exercise will allow spatially-explicit OHAS data to be released to the public with some information about the confidence to which it can be applied. These data will be archived at Portland State University and made available to the public. The information and algorithms can be shared with other agencies collecting and archiving travel data, such as the National Household Travel Survey, metropolitan planning organizations and state departments of transportation, to permit wider dissemination of their data. Title: Wider Dissemination of Household Travel Survey Data Using Geographical Perturbation Methods Author: Clifton, Kelly J., Gehrke, Steven R. Year: 2014 Public agencies spend vast amounts of money collecting information about passenger travel in household travel surveys. These data are valuable for the rich and detailed information they provide, which contribute to regional and statewide travel demand models. These data have utility beyond travel demand modeling in their application to transportation policy and travel behavior research. As the demand on these data increase, so have the quantity of information collected. Detailed geospatial referencing of the home, work and other travel destinations are common practice and permit the integration with other spatially archived data sources, such as land use characteristics, transportation system information, and other built environment, social and economic data. Other public agencies, private consultancies, non-profits and educational institutions may benefit from access to the original data with applications to areas such public health, equity, transportation safety and urban planning. Oregon Modeling Collaborative (OMC) has entered into an agreement with Oregon Modeling Steering Committee (OMSC) to host and make available Oregon Household Activity Survey (OHAS) datasets. But wide distribution of these important and expensive data is limited by the requirement to protect the confidentiality of survey participants, who are guaranteed anonymity in exchange for participation. Data are often aggregated to a geographic level such as Census tracts or transportation analysis zones (TAZs) before disseminating to the public, which limits the utility of this information. This project aims to develop a methodology to permit dissemination of these spatially-explicit data to a wider range of public constituents while at the same time, protecting the identities of study participants. Making use of these data, this project will use geographical perturbation methods to add noise to the original data to protect confidentiality while at the same time allowing the detailed geo-spatial referencing to be included in the disseminated data. The process includes: The coordinates (locations) will be geographically perturbed (masked) so that they do not reveal the identity of the traveler while at the same time retaining spatial relevance and resolution. Here the limits of the perturbation (minimum and maximum displacement) need to be determined that a) ensure confidentiality and b) minimize the errors introduced to the data. The original and perturbed (masked) data will be compared using various statistical approaches to develop a set of confidence measures for different types of transportation applications. For example, geographically perturbed (masked) may be more robust for automobile travel measures, such as vehicle miles traveled (VMT) or transit accessibility than for detailed pedestrian or bicycle trip attributes. This exercise will allow spatially-explicit OHAS data to be released to the public with some information about the confidence to which it can be applied. These data will be archived at Portland State University and made available to the public. The information and algorithms can be shared with other agencies collecting and archiving travel data, such as the National Household Travel Survey, metropolitan planning organizations and state departments of transportation, to permit wider dissemination of their data. Close

• 2. [Article] Understanding Residential Location Choices for Climate Change and Transportation Decision Making: Phase 2 Report

  This research builds on the related Phase 1 project. In this second phase, we continue to study neighborhood and housing preferences that shape the residential location decision process. An online experimental ...

  Citation × Citation Citation Abstract Copy Title: Understanding Residential Location Choices for Climate Change and Transportation Decision Making: Phase 2 Report Author: Clifton, Kelly J., Gehrke, Steven R., Currans, Kristina Marie Year: 2015 This research builds on the related Phase 1 project. In this second phase, we continue to study neighborhood and housing preferences that shape the residential location decision process. An online experimental survey tool is developed to investigate lifestyle preferences and tradeoffs that households make in their location decisions. This computer-aided experimental survey draws upon stated preference methods to engage participants in questions about residential location and transportation options. The survey infrastructure was extensively piloted (6-10% response rate). The 10-minute survey can be deployed for future investigations. This infrastructure is a contribution for the integration of visualized neighborhood typologies, or concepts, which were objectively defined using data from 25 of the most populous metropolitan regions from around the United States. The construct of neighborhoods is based upon national data to account for potential options not currently available in Oregon. These visualizations help ground the survey respondents in the same reality and were carefully crafted to convey various attributes of the built and transportation environment. The initial analysis of the preference data collected in this survey (N=1,035) indicates that the preferences for neighborhood, housing, and transportation characteristics have a greater influence on the preferred neighborhood concept than the more typically used socio-economic characteristics (income, household size, age). Another interesting preliminary finding is that 27% of respondents would prefer to live in a more urban neighborhood than they currently reside. These “urban seeking” respondents had no particular demographic trend, providing little evidence that specific socioeconomic markets had specific preferences for the built environment. Title: Understanding Residential Location Choices for Climate Change and Transportation Decision Making: Phase 2 Report Author: Clifton, Kelly J., Gehrke, Steven R., Currans, Kristina Marie Year: 2015 This research builds on the related Phase 1 project. In this second phase, we continue to study neighborhood and housing preferences that shape the residential location decision process. An online experimental survey tool is developed to investigate lifestyle preferences and tradeoffs that households make in their location decisions. This computer-aided experimental survey draws upon stated preference methods to engage participants in questions about residential location and transportation options. The survey infrastructure was extensively piloted (6-10% response rate). The 10-minute survey can be deployed for future investigations. This infrastructure is a contribution for the integration of visualized neighborhood typologies, or concepts, which were objectively defined using data from 25 of the most populous metropolitan regions from around the United States. The construct of neighborhoods is based upon national data to account for potential options not currently available in Oregon. These visualizations help ground the survey respondents in the same reality and were carefully crafted to convey various attributes of the built and transportation environment. The initial analysis of the preference data collected in this survey (N=1,035) indicates that the preferences for neighborhood, housing, and transportation characteristics have a greater influence on the preferred neighborhood concept than the more typically used socio-economic characteristics (income, household size, age). Another interesting preliminary finding is that 27% of respondents would prefer to live in a more urban neighborhood than they currently reside. These “urban seeking” respondents had no particular demographic trend, providing little evidence that specific socioeconomic markets had specific preferences for the built environment. Close