How to Capture Trips within n-Minute Neighborhoods and Does It Always Work? Threshold Effects of Built Environment on Travel Behaviors
Wenjia Zhang, Peking UniversityShow Abstract
Xueyao Luo, Peking University
Hongmou Zhang (firstname.lastname@example.org), Singapore-MIT Alliance for Research and Technology
Jie Yin, Peking University
Yanwei Chai, Peking University
The planning for n-minute neighborhoods has received intensive discussion in many countries in recent years, but few studies offered quantitative assessment to the guidelines in such planning. In this paper, we propose the first generalizable, measurable, and operable goals of building n-minute neighborhoods. The general principles of a desirable n-minute neighborhood are twofold: 1) it should capture a sufficiently large proportion of residents’ daily trips within this walking- or cycling-scale neighborhood, and 2) it should enable and encourage more non-motorized trips when its residents traveling to the outside of the neighborhood. Using data from a household activity survey with 320 individuals in Beijing, we adopted the gradient boosting decision tree (GBDT) algorithm to investigate the nonlinear impact and threshold effect of the built environment factors on the internal capture rate of nonwork trips (ICR), and on the mode choice of external non-work trips (NM). Our results show that local land use factors, and transit and regional access factors are both the major contributing factors to the ICR, while local land use factors are dominant for improving the NM. Local land use factors, such as public service and business service densities, are positively and nonlinearly related to ICR and NM with thresholds. However, proximity to transit stations has negative impact on improving non-motorized external non-work trips. This paper offers a comprehensive quantitative framework for assessing and improving the built environment for planning n-minute neighborhoods.
Land Use Regression of Long-Term Transportation Data on Metabolic Syndrome Risk Factors in Low-income Communities
Juan Aguilera, University of Texas, El PasoShow Abstract
Soyoung Jeon, New Mexico State University, Main Campus Official Bookstore
Mayra Chavez, University of Texas, El Paso
Gabriel Ibarra-Mejia, University of Texas, El Paso
Leah Whigham, UTHealth School of Public Health
Wen-Whai Li, University of Texas, El Paso
Traffic-related air pollution has been associated with adverse cardiovascular health effects in near-road residents. Transportation parameters are important surrogate variables to determine spatial variation of air pollution and consequential health outcomes. We used land use regression models to explore associations between cardiovascular (metabolic syndrome [MetS]) health outcomes collected from a sample of low-income participants (N=4,959) and transportation parameters within a defined impact zone of a participant’s residence. We hypothesize cardiovascular risk factors are associated with spatially distributed transportation parameters and land-use data. MetS risk factors (waist circumference, blood pressure, triglycerides, HDL-cholesterol, and glucose) were obtained from 4,945 participants between 2014 and 2020 across the city of El Paso, Texas. Traffic-related and land-use variables were acquired from the El Paso MPO and the U.S. Census Bureau within two impact zones of 500m and 1,000m radius, centered at each participants resident’s home latitude and longitude coordinates using GIS. The increase in street length within 500m radius was found to associate with increases in BMI, waist circumference, triglycerides, and glucose ( p <0.05). Glucose showed positive relationships with inverse distance to the nearest international ports of entry ( p =0.02). Also, as the total length of the street increases, the likelihood of a high waist ( p <0.01), high triglycerides ( p =0.03), and low HDL-cholesterol ( p <0.01) also increased. Based on a multivariate regression model, a probability surface map was prepared to show the spatial distribution of likelihood for acquiring MetS in El Paso, TX.
Travel Behavior in Sustainable Communities: The Case of the Sustainable City in Dubai
Alimurtaza Kothawala (email@example.com), University of California, DavisShow Abstract
Giovanni Circella, University of California, Davis
Farzad Alemi, University of California, Davis
Maya Abou-Zeid, American University of Beirut
Tim Rogmans, Zayed University
Karim El-Jisr, SEE Institute
Sustainable communities, big and small, are proliferating in the gulf states of Dubai, Abu Dhabi and Qatar. They incorporate sustainable design elements like water reuse, urban farming, low-carbon transportation, and green building design to economize on resource consumption and keep emissions low. Among the different sustainability elements, sustainable transportation solutions are likely the most challenging to implement and must be tailored to location, size of development, demographics, and the prevalent culture. Literature on the transportation aspects of such developments in the Middle East and North Africa (MENA) region, their sustainability and their effectiveness is limited. In this paper, we cover these aspects in The Sustainable City, a 46 hectare mixed-use development housing 3000 people in the outskirts of Dubai. We survey city residents and employees on their current travel behavior and on their response to alternative mobility options. We found that although residents want to live sustainably and make efforts towards it, their transportation is sustainable only within the bounds of the city. Less sustainable options for external trips involving air travel, regular commuting, and even shorter trips to neighboring communities drive up total transportation emissions. While there is interest in shared mobility options and an electric carsharing service help green some travel, we find that the suburban setting of the development, fewer alternative mobility options, a strong car culture, and integration challenges with neighboring communities and existing land-use patterns are major barriers to choosing sustainable transportation options.
Quantifying the Health Benefits of Transit-Oriented Development: Development and Application of the San Diego Public Health Assessment Model (SD-PHAM)
Lawrence Frank (firstname.lastname@example.org), Urban Design 4 Health, Inc.Show Abstract
Eric Fox, Urban Design 4 Health, Inc.
Jared Ulmer, Vermont Department of Health
James Chapman, Urban Design 4 Health, Inc.
Lindsay Braun, University of Illinois, Urbana-Champaign
As evidence of the health impacts of transportation investments has grown, planners have increasingly used health impact assessments (HIAs) to evaluate transportation plans, projects, and policies. Most HIAs to date, however, have been limited in their ability to quantify health impacts due to a lack of validated methods and tools, scarcity of disaggregate and locally-relevant data, and cost. This paper presents the development and application of a quantitative HIA tool designed to address these and other common limitations of existing HIAs. Developed through a grant from the San Diego Association of Governments and the San Diego County Health and Human Services, the tool is based on detailed modeled regression analyses associating the built environment with physical activity, safety, and respiratory health outcomes in a large sample of California Health Interview Survey participants. The tool allows users to enter built environment characteristics for baseline and future development scenarios and estimate corresponding health impacts. This paper describes the development of this tool and its application to the Palomar Gateway District transit-oriented development in San Diego County. The results suggest that the projected build-out is associated with increased physical activity from walking for transportation, park visitation, and reductions in type 2 diabetes and high blood pressure. Potential for increased exposure to air pollution among children and teens may, however, attenuate some of these benefits. Quantifying both the positive and the negative health outcomes of transportation investments can inform proposals and reduce health risks. This study demonstrates how the application of an evidence-based software tool can support the HIA process and create empirical evidence usable within transportation decisions and planning practice.
The Disconnect Between the Practice’s and Community’s View on Transportation Performance
Carlye Lide, Kimley-Horn and Associates, Inc.Show Abstract
Myriam Igoufe, Dallas Housing Authority
Stephen Mattingly, University of Texas, Arlington
Kate Hyun, University of Texas, Arlington
Recent U.S. Department of Housing and Urban Development (HUD) indices that describe the propensity for transit use and assess transportation costs appear inadequate for outlining the community’s true perceptions of transportation. Ideally, these indices also capture the transportation challenges that communities face in accessing opportunities. The failure to include community input and support in transportation improvement plans can lead to inequitable decision making because performance measures fail to align with community needs. This research seeks to determine if a disconnect between the (1) publicly perceived and (2) measured level of transportation performance exists. The research relies on two HUD transportation indices and a survey distributed throughout the Dallas-Fort Worth region. The researchers perform a cross analysis using the geographical information system (GIS) program, ArcMap, to observe if a correlation between the two data sources exists. Zip codes containing median survey responses of unsatisfied also show transit propensity scores in the 61st to 80th percentile and costs scores in the 81st to 100th percentile range, which indicate high transit propensity and very low costs. Error rates created to outline the disconnect of the two data sources also indicates an 87% and 79% disconnect between the median survey responses and the transportation costs and transit propensity scores, respectively. Overall, the data provided for practitioners in this region does not match the public’s response about their level of satisfaction. This research provides a basis for re-calibrating conventional quantitative tools and standard of performance to reflect public satisfaction and perception of transportation performance.
Neighborhood Effects of Safe Routes to School Programs on the Likelihood of Active Travel to School
Carole Voulgaris, Harvard UniversityShow Abstract
Reyhane Hosseinzade, University of California, Davis
Anurag Pande, California Polytechnic State University, San Luis Obispo
Serena Alexander, San Jose State University
Safe Routes to School programs aim to increasing increase the share of students who commute to school by active modes (e.g., walking and cycling). The purpose of this study is to determine the relationship between the presence of Safe Routes to School programs in a community and the likelihood that children attending school in that community travel to school by active modes. We identified children from households who were included in the 2012 California Household Travel Survey and classified them based on whether they commuted to school by active modes. We identified census tracts with SRTS programs based on the presence of data in the National Center for Safe Routes to School Data Collection System. We estimated a logistic regression model to predict the likelihood that a child commutes to school by active modes, based on the presence of a Safe Routes to School program and controlling for individual, household, and tract characteristics. Findings indicate that longer trip distance and race (relative to white students) are associated with reduced rates of active travel to school, but that these differences are mitigated by the presence of Safe Routes to School programs. We conclude that the effect of SRTS programs might best be described as reducing barriers to active school travel, rather than simply increasing the likelihood of using active modes. Also, the students who experience the greatest barriers to using active modes are likely to experience the greatest benefits from SRTS programs.
Investigating transit-induced commercial gentrification in Charlotte, North Carolina
Chang Liu (email@example.com), North Carolina State UniversityShow Abstract
Eleni Bardaka, North Carolina State University
A number of studies have explored the impacts of transit investments on the values and new entries of commercial properties, while transit-induced commercial gentrification has not been extensively studied. The objective of this research is to investigate the potential effects of the Charlotte light rail (LYNX Blue Line) on nearby businesses and identify signs of commercial gentrification before and after its opening. Commercial gentrification can take multiple forms and can be identified through the changes in both the number and composition of establishments. This study presents the preliminary results of a descriptive analysis of establishments between 2003 and 2017, including measures of business entry, exit, retention rate, and turnover. Businesses are categorized into three sectors (retail, knowledge, and recreation and service). In addition, we look into the changes in the small local establishments in comparison to the other establishments. Our preliminary analysis indicates that the Blue Line is more attractive to new establishments before its opening than the following periods. Then, the opening of Blue Line seems to help the nearby establishments survive in the short term, which is opposite afterwards. We also notice the establishments in the knowledge sector seem to be more influenced by the light rail compared to the other two sectors.
Ridesourcing Demand During Rail Transit Disruptions: A Multilevel Analysis of Neighborhood Effects in Chicago, Illinois
Elisa Borowski, Northwestern UniversityShow Abstract
Jason Soria, Northwestern University
Joseph Schofer, Northwestern University
Amanda Stathopoulos (firstname.lastname@example.org), Northwestern University
New on-demand mobility options, such as ridesourcing services, offer the potential to fill unpredicted gaps in mobility, such as unplanned transit disruptions. In this study, we examine the use of ridesourcing during unexpected rail transit service disruptions across the city of Chicago, which has a long history of racial segregation. Using a natural experiment approach, we identify twenty-eight transit disruption events from November 2018 through October 2019, and changes in ridesourcing demand during these disruptions are quantified and analyzed. By employing a multilevel mixed model, we account for unobserved variability in neighborhood contexts, such as ridership, socio-demographic differences, and mobility opportunity and patterns, recognizing the existence of hierarchical structures in the data. Our findings reveal that individuals use ridesourcing as a gap-filling mechanism during rail transit disruptions, but there is strong variation across situational and locational contexts. Specifically, our results show larger increases in transit disruption responsive ridesourcing during weekdays, nonholidays, and more severe disruptions, as well as in community areas that have higher percentages of white residents and transit commuters, and on the more affluent north side of the city. The findings point to new insights on how ridesourcing complements the existing transport network by providing added capacity during disruptions. Yet, ridesourcing does not appear to bring equal gap filling benefits to low-income communities of color that typically have more limited mobility options. We discuss the implications of this apparent inequity in adaptable mobility and discuss policy recommendations to address it.
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