Infrastructure & Transportation Archives - Page 13 of 20

Travel Mode Choices in Small Cities of China: A Case Study of Changting

Hu, Hong; Xu, Jiangang; Shen, Qing; Shi, Fei; Chen, Yangjin. (2018). Travel Mode Choices in Small Cities of China: A Case Study of Changting. Transportation Research: Part D, 59, 361 – 374.

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Abstract

The existing literature on urban transportation planning in China focuses primarily on large cities and neglects small cities. This paper aims to fill part of the knowledge gap by examining travel mode choice in Changting, a small city that has been experiencing fast spatial expansion and growing transportation problems. Using survey data collected from 1470 respondents on weekdays and weekends, the study investigates the relationship between mode choice and individuals' socio-economic characteristics, trip characteristics, attitudes, and home and workplace built environments. While more than 35 percent of survey respondents are car owners, walk, bicycle, e-bike, and motorcycle still account for over 85 percent of trips made during peak hours. E-bike and motorcycle are the dominant means of travel on weekdays, but many people shift to walking and cycling on weekends, making non-motorized and semi-motorized travel especially important for non-commuting trips. Results of multinomial logistic regression show that: (1) job-housing balance might exert different effects on mode choice in different types of urban areas; (2) negative attitude towards e-bike and motorcycle is associated with more walking and cycling; and (3) land use diversity of workplace is related to commuting mode choice on weekdays, while land use diversities of both residential and activity places do not significantly affect mode choice on weekends. Our findings imply that planning and design for small cities needs to differentiate land use and transportation strategies in various types of areas, and to launch outreach programs to shift people's mode choice from motorized travel to walking and cycling.

Keywords

Urban Transportation; Transportation Planning; Outreach Programs; Choice Of Transportation; Commuting; China; Attitude; Built Environment; Mode Choice; Small Cities; Neighborhood Type; Self-selection; Urban Form; Land-use; Behavior; Impact; Attitudes; Ownership; Workers

Cluster-based LSTM Network for Short-term Passenger Flow Forecasting in Urban Rail Transit

Zhang, Jinlei; Chen, Feng; Shen, Qing. (2019). Cluster-based LSTM Network for Short-term Passenger Flow Forecasting in Urban Rail Transit. Ieee Access, 7, 147653 – 147671.

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Abstract

Short-term passenger flow forecasting is an essential component for the operation of urban rail transit (URT). Therefore, it is necessary to obtain a higher prediction precision with the development of URT. As artificial intelligence becomes increasingly prevalent, many prediction methods including the long short-term memory network (LSTM) in the deep learning field have been applied in road transportation systems, which can give critical insights for URT. First, we propose a novel two-step K-Means clustering model to capture not only the passenger flow variation trends but also the ridership volume characteristics. Then, a predictability assessment model is developed to recommend a reasonable time granularity interval to aggregate passenger flows. Based on the clustering results and the recommended time granularity interval, the LSTM model, which is called CB-LSTM model, is proposed to conduct short-term passenger flow forecasting. Results show that the prediction based on subway station clusters can not only avoid the complication of developing numerous models for each of the hundreds of stations, but also improve the prediction performance, which make it possible to predict short-term passenger flow on a network scale using limited dataset. The results provide critical insights for subway operators and transportation policymakers.

Keywords

Traffic Flow; Neural-network; Prediction; Ridership; Models; Volume; Lstm; Short-term Passenger Flow Forecasting; Urban Rail Transit; K-means Clustering; Deep Learning

Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain

Buszkiewicz, James H.; Bobb, Jennifer F.; 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). Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain. International Journal Of Obesity, 45(9), 1914 – 1924.

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Abstract

Objective To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults. Methods Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values. Results Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg. Conclusions Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Keywords

Body-mass Index; Physical-activity; Food Environment; Structural Racism; Obesity; Neighborhoods; Associations; Health; Walkability; Exposure; Environment Models; Minority & Ethnic Groups; Urban Environments; Regression Analysis; Regression Models; Residential Density; Body Mass Index; Property Values; Body Weight Gain; Government Programs; Body Weight; Electronic Medical Records; Electronic Health Records; Fast Food; Buffers; Real Estate; Body Mass; Body Size; Socioeconomics; Health Care

Does Polycentric Development Produce Less Transportation Carbon Emissions? Evidence from Urban Form Identified by Night-Time Lights Across US Metropolitan Areas

Jung, Meen Chel; Kang, Mingyu; Kim, Sunghwan. (2022). Does Polycentric Development Produce Less Transportation Carbon Emissions? Evidence from Urban Form Identified by Night-Time Lights Across US Metropolitan Areas. Urban Climate, 44.

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Abstract

Identifying the comprehensive metropolitan urban form is important to propose effective policies to mitigate transportation carbon emissions. A publicly accessible night-time light dataset was used to identify urban centers and develop two polycentric indices to compute the composition and configuration of urban form, respectively. We used the most populous 103 U.S. metropolitan statistical areas (MSAs), with their corresponding transportation carbon emissions, polycentric indices, population sizes, gross domestic product (GDP) per capita, and road network densities. We first explored the typology of urban form and classified MSAs into six types based on two polycentric indices. We then introduced correlation analysis and statistical models to test the relationships between polycentric urban form and transportation carbon emissions. We found: (1) more urban centers lead to more emissions (compositional dimension), (2) more spatially distributed urban centers result in less emissions (configurational dimension), and (3) population and GDP per capita are positively related to carbon emissions. These findings suggest the importance of measuring two polycentric dimensions separately but using them together. Urban planners should consider mixed strategies that combine the traditional intra-center-based smart growth principles and the metropolitan-level inter-centers spatial plan to effectively counteract climate change.

Keywords

Polycentric Urban Form; Urban Centers; Carbon Emissions; Night-time Lights; Smart Growth; Climate Change; Co2 Emissions; Spatial Structure; Satellite Imagery; Cities; Patterns; Trends; Growth; Determinants; China

Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression

Hong, E-Sok Andy; Bae, Christine. (2012). Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression. Transportation Research Record, 2270, 59 – 66.

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Abstract

The increase in urban bicycling facilities, raises public health concerns for potential exposure of bicyclists to traffic emissions. For an assessment of bicyclists' exposure to local traffic emissions, a hybrid approach is presented; it combines personal monitoring and a land use regression (LUR) model. Black carbon, a proxy variable for traffic-related air pollution, was measured with an Aethalometer along the predesignated bicycle route in Seattle, Washington, for 10 days, during a.m. and p.m. peak hours (20 sampling campaigns). Descriptive statistics and three-dimensional pollution maps were used to explore temporal variations and to identify pollution hot spots. The LUR model was developed to quantify the influence of spatial covariates on black carbon concentrations along the designated route. The results indicated that the black carbon concentrations fluctuated throughout the sampling periods and showed statistically significant diurnal and monthly patterns. The hot spot analysis suggests that proximity to traffic and other physical environments have important impacts on bicyclists' exposure and demand further investigation on the localized effects of traffic emissions on exposure levels. The LUR model explains 46% of the variations in black carbon concentrations, and significant relationships are found with types of bicycle route facility, wind speed, length of truck routes, and transportation and utility land uses. This research is the first application of the LUR approach in quantifying bicyclists' exposure to air pollution in transport microenvironments. This study provides a rationale for encouraging municipalities to develop effective strategies to mitigate the health risks of exposure to local traffic emissions in complex urban bicycling environments.

Keywords

Particulate Matter; Diesel Exhaust; Health; Model; Particles; Asthma; City

Quantifying The Impacts Of Failures Of Departments Of Transportation Building Systems On Road System Users

Gatti, Umberto C.; El-anwar, Omar; Migliaccio, Giovanni C.; Lin, Ken-yu; Medina, Yvonne. (2014). Quantifying The Impacts Of Failures Of Departments Of Transportation Building Systems On Road System Users. Transportation Research Record, 2440, 85 – 93.

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Abstract

Because of the financial crisis of 2007 to 2008 and the subsequent economic downturn, funding for transportation agencies has been consistently reduced. This lack of funds prevents the building assets of transportation agencies from being efficiently maintained, so failures may occur that discontinue employees' operations and activities and affect transportation system users. Thus, to maximize the use of available funding, it is compelling to create innovative tools and techniques capable of estimating how potential failures can affect employees' activities and, eventually, transportation system users. Facility managers and decision makers could use such estimates to make decisions on maintenance of building assets that would minimize the risks of disruptions to employees and transportation system users. Among the capital assets of the Washington State Department of Transportation (DOT), transportation equipment fund (TEF) shops are crucial in ensuring timely and effective care and maintenance of the majority of state vehicles and equipment Therefore, any disruption of the operations of TEF shop facilities could significantly affect not only the Washington State DOT's vehicles and equipment maintenance but also the department's ability to fulfill its core mission. Given the importance of TEF shops, this exploratory case study investigates the failures that have occurred or are likely to occur in these facilities and employs discrete-event simulation to quantify the consequences of such failures on the shop activities and road users.

Keywords

Simulation

Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes

Chen, Peng; Shen, Qing. (2016). Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes. Accident Analysis & Prevention, 86, 239 – 246.

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Abstract

This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. (C) 2015 Elsevier Ltd. All rights reserved.

Keywords

Cycling Injuries; Traffic Accidents; Transportation Planning; Data Analysis; Employment; Built Environment; Cyclist Injury Severity; Generalized Additive Model; Generalized Ordered Logit Model; Ordered Response Model; United-states; Helmet; Frameworks; Driver; Risk

Economic Impact of High-Speed Rail on Household Income in China

Sun, Feiyang; Mansury, Yuri S. (2016). Economic Impact of High-Speed Rail on Household Income in China. Transportation Research Record, 2581, 71 – 78.

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Abstract

Although developed only in the past 20 years, Chinese high-speed rail (HSR) has overtaken many of its forerunners in its unprecedented scale. However, such a scale raises questions about its implications for regional economic development. Previous studies have discussed the impact of HSR at the regional and city levels, but few have addressed its impact on the individual level, which is crucial for understanding the distribution of the impact. To fill the gap, this study focused on the economic impact of recent HSR development between 2009 and 2012 on Chinese household income and discussed its significance, magnitude, and distribution. The survey data from the China Family Panel Survey were used and a difference-in-differences approach was implemented. Two key explanatory variables, weighted average travel time and probability of living proximate to HSR stations, were included in the models to examine the direct and spillover impacts of HSR. The study shows that these impacts both contribute to the HSR impact but affect urban and rural regions and production sectors differently. In particular, the spillover effect or the agglomeration effect contributes the most and favors more urbanized regions with stronger service sectors. As a consequence, although HSR plays a positive role in stimulating the regional economy, it may further widen the gap between developed regions and underdeveloped regions. From the analyses, it is concluded that HSR projects need more comprehensive studies of the full spectrum of its impact to ensure both economic growth and regional balance and coordination.

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