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Browsing by Subject "Pedestrian"

Now showing 1 - 4 of 4
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    Access Across America: Walk 2022 Data
    (2024-10-21) Owen, Andrew; Liu, Shirley Shiqin; Jain, Saumya; Hockert, Matthew; Lind, Eric; owenx148@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
    These data were created as part of a study that examines the accessibility to jobs by walking or rolling across the United States. It is the most detailed evaluation to date of access to jobs by walking, and it allows for a direct comparison of the walkability of America's metropolitan areas. These data are part of a longitudinal study. Walk/roll data for additional years can be found in the Accessibility Observatory Data collection: https://hdl.handle.net/11299/200592
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    HarMar Mall Redevelopment
    (Hubert H. Humphrey School of Public Affairs, 2012-08-31) Carlton, Zachary
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    Nonmotorized Transportation Pilot Program Evaluation Study, Phase 2
    (Center for Transportation Studies, University of Minnesota, 2011-05) Götschi, Thomas; Krizek, Kevin J.; McGinnis, Laurie; Lucke, Jan; Barbeau, Joe
    The Nonmotorized Transportation Pilot Program (NTPP) is a congressionally mandated program (SAFETEA-LU Section 1807) that, since 2006, has provided roughly $25 million each to four communities—Columbia, Missouri; Marin County, California; Minneapolis area, Minnesota; Sheboygan County, Wisconsin—to spur levels of walking and cycling via a variety of planning measures. The University of Minnesota Center for Transportation Studies is leading the community-wide population surveys for the Nonmotorized Transportation Pilot Program (NTPP), specifically in phase 2, to measure changes in levels of walking and bicycling as a result of the enhanced conditions for walking and bicycling. To evaluate impacts of the program, two community-wide surveys were conducted before (phase 1: 2006) and after (phase 2: 2010) the pilot program. This report describes the evaluation efforts based on community-wide population surveys. In contrast to project-specific evaluations, community-wide surveys serve the purpose of representatively assessing community-wide levels of nonmotorized travel behavior, which serve as the foundation for subsequent benefit calculations. The survey in phase 1 consisted of a short mail-out questionnaire and a computer assisted telephone interview (CATI) among respondents to the short questionnaire. In phase 2 the short questionnaire was integrated in the CATI. The final sample in phase 1 consisted of 1279 complete records and in phase 2 of 1807 complete records. Statistical analysis focused on evaluating differences between phase 1 and phase 2 in the core variables on nonmotorized travel behavior. The detailed analysis did not reveal any consistent or statistically significant differences between phases 1 and 2. It is important to point out that the inability to detect significant patterns of change is not synonymous to no change occurring. The report discusses some of the factors that make this type of research challenging.
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    Using an empirical model of human turning motion to aid heading estimation in a personal navigation system
    (2013-12) Jakel, Tom Bryan
    With the adoption of Global Navigation Satellite Systems in smart phones, soldier equipment, and emergency responder navigation systems users have realized the usefulness of low cost Personal Navigation Systems. The state-of-the-art Personal Navigation System is a unit that fuses information based on external references with a low cost IMU. Due to the size, weight, power, and cost constraints imposed on a pedestrian navigation systems as well as current IMU performance limitations, the gyroscopes used to determine heading exhibit significant drift limiting the performance of the navigation system. In this thesis biomechanical signals are used to predict the onset of pedestrian turning motion. Experimental data from eight subjects captured in a gait laboratory using a Vicon motion tracking unit is used for validation. The analysis of experimental data shows the heading computed by turn prediction augmented integration is more accurate than open loop gyro integration alone.