Infrastructure & Transportation Archives - Page 13 of 20

Increased Walking’s Additive and No Substitution Effect on Total Physical Activity

Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Increased Walking’s Additive and No Substitution Effect on Total Physical Activity. Medicine & Science In Sports & Exercise, 50(3), 468 – 475.

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Abstract

Purpose We assessed the associations between a change in time spent walking and a change in total physical activity (PA) time within an urban living adult sample to test for additive or substitution effects. Methods Participants living in the greater Seattle area were assessed in 2008-2009 and again 1-2 yr later (2010-2011). At each time point, they wore accelerometers and GPS units and recorded trips and locations in a travel diary for seven consecutive days. These data streams were combined to derive a more objective estimate of walking and total PA. Participants also completed the International Physical Activity Questionnaire to provide self-reported estimates of walking and total PA. Regression analyses assessed the associations between within-participant changes in objective and self-reported walking and total PA. Results Data came from 437 participants. On average, a 1-min increase in total walking was associated with an increase in total PA of 1 min, measured by objective data, and 1.2-min, measured by self-reported data. A similar additive effect was consistently found with utilitarian, transportation, or job-related walking, measured by both objective and self-reported data. For recreational walking, the effect of change was mixed between objective and self-reported results. Conclusion Both objective and self-reported data confirmed an additive effect of utilitarian and total walking on PA.

Keywords

Accelerometers; Global Positioning System; Metropolitan Areas; Questionnaires; Recreation; Self-evaluation; Time; Walking; Physical Activity; Accelerometer; Gps; Ipaq; Longitudinal Study; Self-reported Measures; Light-rail Construction; Built Environment; Accelerometer Data; Older-adults; Urban Form; Transit Use; Travel; Neighborhood; Interventions; Calibration

Rebaselining Asset Data for Existing Facilities and Infrastructure

Abdirad, Hamid; Dossick, Carrie Sturts. (2020). Rebaselining Asset Data for Existing Facilities and Infrastructure. Journal Of Computing In Civil Engineering, 34(1).

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Abstract

This paper introduces rebaselining as a workflow for collecting reliable and verifiable asset management data for existing facilities and infrastructure. Reporting on two action research case studies with two public owners in the US, this research structures rebaselining in four phases: (1) preparing technology enablers, (2) collecting data from existing documents, (3) conducting field verification, and (4) updating asset management databases. These workflows address some of the common challenges in managing existing assets, including the fast-paced changes in asset data requirements, the inaccuracies in data and documentation of these existing assets portfolios, and the need to update data and documents over their life cycle. The findings set the groundwork for implementing workflow by mapping the rebaselining business processes in each phase, listing the technological requirements for these processes, and explaining the feasibility and examples of customizing building information modeling (BIM) platforms for rebaselining workflows. This customization of BIM platforms aims to offer simplified solutions that reduce the facility management staff's need for advanced BIM software knowledge.

Keywords

Asset Management; Building Management Systems; Business Data Processing; Database Management Systems; Facilities Management; Production Engineering Computing; Project Management; Risk Analysis; Software Tools; Reliable Asset Management Data; Verifiable Asset Management Data; Action Research Case Studies; Public Owners; Research Structures; Technology Enablers; Asset Management Databases; Facility Management Staff; Rebaselining Workflows; Technological Requirements; Rebaselining Business Processes; Existing Assets Portfolios; Documentation; Asset Data Requirements; Managing Existing Assets; Information; Bim; Existing Buildings; Infrastructure; Asset Data; Rebaselining

Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age

Buszkiewicz, James H.; Bobb, Jennifer F.; Kapos, Flavia; Hurvitz, Philip M.; Arterburn, David; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Cruz, Maricela; Gupta, Shilpi; Lozano, Paula; Rosenberg, Dori E.; Theis, Mary Kay; Anau, Jane; Drewnowski, Adam. (2021). Differential Associations of the Built Environment on Weight Gain by Sex and Race/Ethnicity but Not Age. International Journal Of Obesity, 45(12), 2648 – 2656.

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Abstract

Objective To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults. Methods Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values. Results Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures. Conclusion The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

Keywords

Body-mass Index; Socioeconomic-status; Food Environment; Obesity; Health; Outcomes; Scale; Risk; Minority & Ethnic Groups; Urban Environments; Etiology; Demographics; Sex; Residential Density; Supermarkets; Age; Race; Ethnicity; Property Values; Body Weight Gain; Electronic Medical Records; Fast Food; Electronic Health Records; Real Estate; Subgroups; Demography; Trajectory Analysis; Weight

Ensuring Equitable Transportation For The Disadvantaged: Paratransit Usage By Persons With Disabilities During The Covid-19 Pandemic.

Wang, Yiyuan; Shen, Qing; Abu Ashour, Lamis; Dannenberg, Andrew L. (2022). Ensuring Equitable Transportation For The Disadvantaged: Paratransit Usage By Persons With Disabilities During The Covid-19 Pandemic. Transportation Research Part A: Policy & Practice, 159, 84 – 95.

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Abstract

Paratransit services developed under the Americans with Disabilities Act are a critical transportation means for persons with disabilities to meet their basic needs, but the COVID-19 pandemic posed an unprecedented challenge to service providers. To safeguard transportation equity, this study used complete records of service trips and riders obtained from the Access Transportation Program in the Seattle region for an empirical analysis aimed at answering two research questions. First, how did the ridership and trip purposes of paratransit change after the outbreak of COVID-19? Second, what factors explained the users' changing levels of service usage in response to the pandemic? Statistical methods, including a Hurdle model, were employed as the analytical tools. The results show that paratransit ridership dramatically decreased during 2020 with the most substantial reductions of working and non-essential personal trips, and that most of the remaining trips were for medical purposes. The results also indicate that riders' service usage during the pandemic was associated with their sociodemographic characteristics, disability conditions, and pre-pandemic travel demand. When controlling for other factors, riders who lived in neighborhoods with lower income and lower access to personal vehicles were more dependent on the service. Based on the empirical findings, we recommend that when developing plans for future disruptive events, public transit agencies should promptly implement safety measures, identify and prioritize neighborhoods that are most in need of mobility services, and actively pursue collaboration with other organizations for innovative service delivery options.

Keywords

Covid-19 Pandemic; Public Transit; People With Disabilities; Americans With Disabilities Act Of 1990; Public Transit Ridership; Paratransit Services; Seattle (wash.); Americans With Disabilities Act (ada); Hurdle Model; Paratransit; Transportation Equity; Mobility; Justice

How to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, Washington

Jiao, Junfeng; Moudon, Anne V.; Ulmer, Jared; Hurvitz, Philip M.; Drewnowski, Adam. (2012). How to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, Washington. American Journal Of Public Health, 102(10), E32 – E39.

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Abstract

Objectives. We explored new ways to identify food deserts. Methods. We estimated physical and economic access to supermarkets for 5 low-income groups in Seattle-King County, Washington. We used geographic information system data to measure physical access: service areas around each supermarket were delineated by ability to walk, bicycle, ride transit, or drive within 10 minutes. We assessed economic access by stratifying supermarkets into low, medium, and high cost. Combining income and access criteria generated multiple ways to estimate food deserts. Results. The 5 low-income group definitions yielded total vulnerable populations ranging from 4% to 33% of the county's population. Almost all of the vulnerable populations lived within a 10-minute drive or bus ride of a low-or medium-cost supermarket. Yet at most 34% of the vulnerable populations could walk to any supermarket, and as few as 3% could walk to a low-cost supermarket. Conclusions. The criteria used to define low-income status and access to supermarkets greatly affect estimates of populations living in food deserts. Measures of access to food must include travel duration and mode and supermarket food costs.

Keywords

Neighborhood Characteristics; Store Availability; Accessibility; Consumption; Disparities; Environment; Location; Fruit; Pay

How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales

Hong, Jinhyun; Shen, Qing; Zhang, Lei. (2014). How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales. Transportation, 41(3), 419 – 440.

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Abstract

Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor-if any-influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.

Keywords

Land-use; Urban Form; Multilevel Models; Physical-activity; Neighborhood; Choice; Impact; Specification; Accessibility; Causation; Built Environment; Travel Behavior; Self-selection; Spatial Autocorrelation; Bayesian Hierarchical Model

Effects of the Built Environment on Automobile-involved Pedestrian Crash Frequency and Risk

Chen, Peng; Zhou, Jiangping. (2016). Effects of the Built Environment on Automobile-involved Pedestrian Crash Frequency and Risk. Journal Of Transport & Health, 3(4), 448 – 456.

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Abstract

This area-based study explores the relationship between automobile-involved pedestrian crash frequency versus risk and various built environment factors such as road network and land use. The methodology involves the use of Bayesian hierarchical intrinsic conditional autoregressive model, which accounts for unobserved heterogeneities and spatial autocorrelations. The city of Seattle is selected for this empirical study, and the geospatial unit of analysis is traffic analysis zone. The primary data were obtained from collision profiles available at the Seattle Department of Transportation. The major findings of this study include: (1) the densities of 4-way intersections and more than 5-way intersections and land use mixture are positively correlated with the pedestrian crash frequency and risk; (2) sidewalk density and the proportion of steep areas are negatively associated with the pedestrian crash frequency and risk; (3) areas with a higher bus stop density are likely to have more pedestrian crashes; (4) areas with a greater proportion of industrial land use have lower pedestrian crash frequency; (5) areas with an averagely higher posted speed limit has higher pedestrian crash risk; (6) areas with a higher employment density has lower pedestrian crash risk; (7) the mode share of walking and the total number of trips are positively correlated with the pedestrian crash frequency, and the total number of trips is negatively correlated with the pedestrian crash risk. These findings provide support for planning policy making and road safety programs. Local authorities should improve walkability by providing more sidewalks and separate travel lanes for motorized traffic and pedestrians in areas with different land use purposes. Compact development should be encouraged to support building a safe walking environment. (C) 2016 Elsevier Ltd. All rights reserved.

Keywords

Spatial-analysis; Urban Form; Land-use; Model; Counts; Transportation; Severity; Bicycle; Safety; Travel; Pedestrian Crash Frequency; Pedestrian Crash Risk; Built Environment; Spatial Autocorrelation; Road Network; Land Use

Comparing Travel Mode and Trip Chain Choices Between Holidays and Weekdays

Yang, Liya; Shen, Qing; Li, Zhibin. (2016). Comparing Travel Mode and Trip Chain Choices Between Holidays and Weekdays. Transportation Research Part A: Policy & Practice, 91, 273 – 285.

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Abstract

Choices of travel mode and trip chain as well as their interplays have long drawn the interests of researchers. However, few studies have examined the differences in the travel behaviors between holidays and weekdays. This paper compares the choice of travel mode and trip chain between holidays and weekdays tours using travel survey data from Beijing, China. Nested Logit (NL) models with alternative nesting structures are estimated to analyze the decision process of travelers. Results show that there are at least three differences between commuting-based tours on weekdays and non-commuting tours on holidays. First, the decision structures in weekday and holiday tours are opposite. In weekday tours people prefer to decide on trip chain pattern prior to choosing travel mode, whereas in holiday tours travel mode is chosen first. Second, holiday tours show stronger dependency on cars than weekday tours. Third, travelers on holidays are more sensitive to changes in tour time than to the changes in tour cost, while commuters on weekdays are more sensitive to tour cost. Findings are helpful for improving travel activity modeling and designing differential transportation system management strategies for weekdays and holidays. (C) 2016 Elsevier Ltd. All rights reserved.

Keywords

Choice Of Transportation; Transportation Management; Voyages & Travels; Travel Costs; Travel Time (traffic Engineering); Decision Structure; Nested Logit Model; Policy; Travel Behavior; Patterns; Behavior; Time

Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary

Kang, Mingyu; Moudon, Anne V.; Hurvitz, Philip M.; Saelens, Brian E. (2018). Capturing Fine-Scale Travel Behaviors: A Comparative Analysis between Personal Activity Location Measurement System (PALMS) and Travel Diary. International Journal Of Health Geographics, 17(1).

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Abstract

BackgroundDevice-collected data from GPS and accelerometers for identifying active travel behaviors have dramatically changed research methods in transportation planning and public health. Automated algorithms have helped researchers to process large datasets with likely fewer errors than found in other collection methods (e.g., self-report travel diary). In this study, we compared travel modes identified by a commonly used automated algorithm (PALMS) that integrates GPS and accelerometer data with those obtained from travel diary estimates.MethodsSixty participants, who made 2100 trips during seven consecutive days of data collection, were selected from among the baseline sample of a project examining the travel behavior impact of a new light rail system in the greater Seattle, WA (USA) area. GPS point level analyses were first conducted to compare trip/place and travel mode detection results using contingency tables. Trip level analyses were then performed to investigate the effect of proportions of time overlap between travel logs and device-collected data on agreement rates. Global performance (with all subjects' data combined) and subject-level performance of the algorithm were compared at the trip level.ResultsAt the GPS point level, the overall agreement rate of travel mode detection was 77.4% between PALMS and the travel diary. The agreement rate for vehicular trip detection (84.5%) was higher than for bicycling (53.5%) and walking (58.2%). At the trip level, the global performance and subject-level performance of the PALMS algorithm were 46.4% and 42.4%, respectively. Vehicular trip detection showed highest agreement rates in all analyses. Study participants' primary travel mode and car ownership were significantly related to the subject-level mode agreement rates.ConclusionsThe PALMS algorithm showed moderate identification power at the GPS point level. However, trip level analyses found lower agreement rates between PALMS and travel diary data, especially for active transportation. Testing different PALMS parameter settings may serve to improve the detection of active travel and help expand PALMS's applicability in geographically different urbanized areas with a variety of travel modes.

Keywords

Transportation Planning; Public Health; Accelerometers; Global Positioning System; Voyages & Travels; Cycling; Algorithms; Accelerometer; Automated Algorithm; Gis; Gps; Places; Trips; Global Positioning Systems; Physical-activity; Data-collection; Health Research; Gps Data; Accelerometry; Validity

Urban Structure and its Influence on Trip Chaining Complexity in the Mexico City Metropolitan Area

Bautista-Hernández, Dorian. (2020). Urban Structure and its Influence on Trip Chaining Complexity in the Mexico City Metropolitan Area. Urban, Planning And Transport Research, 8(1), 71 – 97.

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Abstract

This project studies the relationship between the urban structure of the Mexico City Metropolitan Area (MCMA) and two aspects of commuter travel patterns: (1) number of stops in a tour and (2) complexity of trip chaining. Two regression models were explored, one for each dependent variable of interest. The analysis was applied for car drivers, transit users and travelers with mixed transportation separately. Covariates include individual, household, travel and urban form variables, which showed differential effects according to the transportation mode. According to the number of significant covariates, it can be said that there is less impact of urban form on trip generation and complexity of travel for car drivers (only mixed land use at destination being significant for complexity of travel) and mixed transportation (being only significant job access for complexity of travel) than for transit users (being significant job access, population density, mixed land use at origin for extra trip, number of trips and complexity of travel). The directions of these effects vary according to the transportation mode and are discussed in terms of reported literature.

Keywords

Trip Generation; Urban Structures; Chaining; Drivers; Population Density; Land Use; Regression Analysis; Regression Models; Transportation; Travel; Complexity; Automobile Drivers; Metropolitan Areas; Travel Patterns; Urban Areas; Dependent Variables; Mexico