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Publication Search Results

Now showing 1 - 9 of 9
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Breaking Myths behind "Bikelash": Empirical analyses on the role of protected bike lanes on creating a sustainable, equitable, and safer transportation environment

2023-12-10 , Hwang, Uijeong

While cycling is recognized as an eco-friendly alternative to carbon-emitting vehicles and a facilitator of physical activity, opposition to cyclists and bike lanes—termed “bikelash”—persists. This resistance stems from various concerns, ranging from the belief that bike lanes are underutilized and thus a waste of public space to fears that they may exacerbate traffic congestion or even contribute to urban gentrification. Through three detailed studies, this dissertation aims to provide empirical evidence challenging common perceptions and to reshape the narrative surrounding bike lanes. The first study investigates how bike lanes sway individuals' transportation choices, especially favoring non-automotive travel. It employs a novel approach by conducting a route-level analysis using origin-destination data from household travel surveys to simulate potential cycling routes. This study finds that bike lanes significantly encourage the use of walking, cycling, and public transit, thereby reducing car dependency. Notably, it demonstrates the potential of bike lanes to bridge mobility gaps in diverse socio-economic settings, even in underserved neighborhoods. The second study examines how the perception of streetscapes and different types of bike lanes interact to influence cycling behaviors. Utilizing computer vision to interpret perceptual attributes from crowdsourced street view images, the research reveals that the presence and type of bike lanes significantly influence cycling frequency, moderated by the visual perception of streetscape safety. Protected bike lanes are shown to be more effective in areas perceived as less safe, emphasizing their role in equitable transportation. The final paper delves into the safety impact of bike lanes, particularly focusing on near-miss incidents. It utilizes crowdsourced data to examine the risk of near misses in relation to street design and types of bike lanes. The findings indicate that protected bike lanes significantly reduce the risk of near misses, while striped lanes adjacent to street parking increase safety hazards. This challenges existing assumptions about bike lane safety and calls for a strategic shift towards protected bike lanes. This dissertation contributes to practical applications by providing critical empirical evidence to guide urban infrastructure planning and policymaking. The findings support a shift towards protected bike lanes, emphasizing their role in enhancing safety and increasing cycling frequency. The dissertation advocates for a holistic approach in urban transportation planning, promoting inclusive, sustainable, and safer urban environments.

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Assessing mental wellbeing in urban areas using social media data: understanding when and where urbanites stress and de-stress

2021-12-10 , Dutt, Florina

Are Americans more stressed out by living in dense, urbanized areas or less dense, car-oriented areas? To answer this question, can we use people's expressions of stress in different environments to understand what kinds of spaces help them de-stress? This study uses stress levels of geolocated tweets to help us answer such inquiries and resolve the longstanding disparities between the field of psychology and urban planning about mental health impacts of cities. This is important because more than 75 percent of Americans are moderately stressed. Long-term stress is associated with mental health disorders, including sleeplessness, anxiety, and depression. Additionally, chronic stress is linked to physical ailments, including high blood pressure, cardiovascular diseases, and diabetes. The psychology literature claims that urban areas witness elevated levels of mental health problems, manifested as stress, mood disorders, and anxiety issues. Density, crowding, traffic, crime, and pollution are identified as stressors associated with urban living conditions. Contending this claim, the urban planning literature positions stress in the context of longer commutes, lack of accessibility, and social isolation that comes with suburban living conditions. Urban Planners and urban designers have advocated for density. With rapid urbanization, 60 percent of the world population will live in urban areas by 2030, making it crucial for urban planners to address these disparities to support the mental wellbeing of the urbanites. This research uses multi-headed attention transformer model to classify tweets (token sequences), and assesses the stress levels of custom-defined assessment grids of ten acres within the city area of Atlanta and Boston. The assessed stress level of these assessment grids is called the mental wellbeing score (MWS). Mental wellbeing score is defined in this research as a measure of `mental wellbeing' of any given grid (higher score is better). Using this measure, the research investigates the relationship between mental wellbeing and built environment characteristics in urban areas to uncover the impact of long-term stress triggered by the conditions of the built environment in urban settings. In summary, the results of the exploration shed light on three critical aspects: 1. Mental wellbeing score increases with increasing urbanness. 2. The mental wellbeing score increases with the increase in the diversity of escape facilities, including green parks, open spaces, and other points of interest. 3. The mental wellbeing score is positively impacted by accessible high-density spaces with high symbolic value. The research also investigates the impact of safety perception and socio-economic status on mental wellbeing scores. The results show that addressing socio-economic disparity, crime, and investment in green infrastructure can improve mental wellbeing of urbanites. The methods and findings of the research show that 'urban areas' can positively impact mental health if designed appropriately. Furthermore, this study can empower urban planners and policymakers to develop tools to assess the mental wellbeing of urbanites, adjust infrastructure needs, and improve the urban amenities that support mental wellbeing.

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Will millennials stay in cities and travel without cars?

2018-08-24 , Lee, Yongsung

Will millennials stay in cities and travel without cars? To answer this question, this dissertation examines heterogeneity in modality styles and residential preferences in a sample of millennials and members of Generation X in California in 2015. It finds that both sociodemographic/ economic characteristics and attitudes about various dimensions (e.g., preferred built environments, travel modes, and car ownership) account for the heterogeneous behavioral and choice patterns in the sample. These findings provide insights on the ways millennials may switch their modality styles or residential preferences in response to changes in sociodemographic/economic conditions or attitudes in the coming years. This dissertation highlights the use of latent-class approaches as effective for the identification of heterogeneity in tastes related to the travel behaviors and location choices of millennials. Researchers are advised to apply these approaches to longitudinal analyses. This research also informs planners and policymakers of dynamic changes in the form or share of latent classes in their region.

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Explore pedestrian route choice preferences by demographic groups: analysis of street attributes in Chicago

2023-05-15 , Lieu, Seung Jae

Traditional transit accessibility models often overlook travel behavior and fine-grained transit characteristics experienced during first and last-mile walking. Existing models typically assume travelers choose the shortest walking path to minimize travel time, but studies suggest pedestrians do not always follow this pattern. This study investigates pedestrian route choice preferences in Chicago, Illinois, using a diverse dataset of home-based work walking trajectories collected from a smartphone application. The impact of street attributes on route choice is examined, and a comparison is made of how built environment factors influence preferences among different demographic groups. A path-size logit model with a constrained enumeration approach-based choice set is employed for analysis. This study also addresses two gaps in pedestrian route choice research. First, unlike most studies that use data constrained to a particular study area or limited participant groups, this research employs a diverse dataset of actual walking trajectories covering a wide range of destinations and participant profiles. Second, this study utilizes GPS data, offering more accurate route choice analysis compared to questionnaires. Such surveys may suffer from recall bias, and they may not capture route choice variability across different times and days. The findings from this study indicate that factors such as distance, the number of amenities and establishments, sky visibility, greenery, and park accessibility along the route significantly influence route choice. While route distance and the number of establishments have a negative impact on preference, other factors positively affect route selection. To compare the effect of each variable across gender, age, and income, this study has operationalized the coefficients to use the concept of ‘equivalent walking distance.' This measure quantifies the incremental disutility resulting from various route attributes, represented as an equivalent increase or decrease in walking distance. The analysis shows that male pedestrians are more willing to walk further when there is greater sky visibility. Similarly, individuals aged over 30 years old tend to walk longer distances with increased sky visibility. Notably, we found no significant variables influencing route choice among different income groups.

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Measuring Street-Level Walkability through Big Image Data and Its Associations with Walking Behavior

2021-07-26 , Koo, Bon Woo

The built environment characteristics associated with walkability range from neighborhood-level urban form factors to street-level urban design factors. However, many existing walkability measures are primarily based on neighborhood-level factors and lack consideration for street-level factors. Neighborhood-level factors alone can be limited in representing various needs of pedestrians. While pedestrians seek to fulfill their needs for accessibility, safety, comfort, and pleasurability, neighborhood-level factors tend to be limited to capturing the accessibility of the built environment (i.e., having places to go to and being physically connected to those places). The high-order needs (i.e., safety from crime, comfort from vehicular traffic, and aesthetic pleasurability) can be more closely proxied by street-level factors. Also, past studies suggested that certain street-level factors may weaken (or strengthen) the effect of neighborhood-level factors on walking behavior, which can be particularly important for disadvantaged populations who tend to be less responsive to neighborhood-level factors. However, measuring street-level factors often requires extensive manual labor and tends to be resource-intensive, resulting in the omission of street-level factors in widely used walkability measures such as Walk Score. This dissertation uses street view images and computer vision to overcome these challenges in measuring street-level factors and expands the literature by examining their association with walking mode choice. This dissertation first applies a pre-trained computer vision model to street view images and measure mesoscale (i.e., a midlevel spatial scale between macro and microscale) factors of walkability. It finds that the mesoscale factors have a significant contribution to walking mode choice models, and the contribution is greater than that from neighborhood-level factors. Next, the dissertation develops a method for automatically auditing walkability factors in microscale (i.e., the smallest spatial scale that pertains to the most fine-grain design details and their qualities) using the combination of computer vision, street view images, and geographic information systems. The validation results demonstrate moderate to high reliability between audit results by automated audit method and a trained human auditor. Finally, the dissertation uses automatically audited microscale factors to unpack the reasons for the weaker relationship between neighborhood-level factors and disadvantaged populations’ walking behavior. The result shows that microscale factors play a sizable role in moderating the effect of neighborhood-level factors. Collectively, this dissertation demonstrates the potential of using street view images and computer vision for research on the built environment-walking relationship and for collecting data on street-level factors over expansive geographic areas, a task that has traditionally been prohibitively expensive. The theoretical and methodological contributions of this dissertation help urban planners and designers understand the physical condition of their cities at street-level and make targeted interventions that are effective and equitable.

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The interaction between land use and transportation in the era of shared autonomous vehicles: a simulation model

2017-05-19 , Zhang, Wenwen

The promising Shared Autonomous Vehicle (SAV) system will inevitably lead to changes in urban land use. Despite recent proliferating studies regarding SAVs, it remains unclear how this affordable and environmentally friendly travel mode will influence residential and commercial location choices and potentially transform urban form. This dissertation develops a discrete event based SAV simulation and implements the model using the transportation network, travel demand, and land use data from Atlanta Metropolitan area. The model is then integrated with residential and employment (re)location choice models to explore how the SAV system will affect urban parking, residential land use, as well as employment agglomeration patterns. The results suggest SAV can significantly reduce parking demand by over 90%. Additionally, the simulation results also indicate the system will not induce residential sprawl into rural areas. Finally, it appears that SAV will accelerate the existing deindustrialization process in cities. The results of this study can provide implications for devising more sustainable land use policies in the era of SAVs.

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Investigating Travel Behavior in Transit-Oriented Development: Toward Sustainable and Multimodal Mobility

2021-12-14 , Choi, Yunkyung

An extensive literature has shown that transit-oriented development residents (TOD) have lower automobile use and diverse travel modes due to easy access to transit, better walkability, and proximity to various amenities. While such benefits of TOD are generally expected, the degree to which TODs influence travel behavior is still debatable. Besides, TOD implementation differs by context, and not all transit areas are developed along TOD principles. This variation in transit areas leads to different impacts on transportation outcomes. Although different TOD typologies have been developed in past studies, they are limited to a particular city or region. The other ongoing debate in land use and travel behavior field is the emergence of new mobility services that enable users to utilize a mode of transport on an as-needed basis. Recent advances in information technologies have facilitated new mobility services that meet travelers’ diverse needs, such as transportation network companies (TNCs), ridesharing, car sharing, bike sharing, microtransit, and shared autonomous vehicles. While new mobility services are expected to play an important role—either positive or negative—in planning how TODs can be implemented, the impacts and consequences of such services on traditional modes of transport such as public transit are still not well understood. In doing so, this dissertation investigates different modes of transportation in TOD areas by posing the following research questions: 1) do people walk more in transit-oriented developments? 2) are residents more multimodal in transit-oriented developments? and 3) what is the potential impact of new mobility services on public transit demand? For the first question, this dissertation addresses the effect of rail transit access on walking behavior in TOD areas. TODs are compared to other similar areas without rail transit access to determine whether people are more likely to walk in TODs for purposes other than transit use in Atlanta. The second question is addressed by identifying different TOD types on their impacts on residents’ multimodal behavior to capture various conditions of existing TODs and their heterogeneous outcomes. This research identifies different types of 4,400 transit areas—a half-mile buffer area from rail station—in the U.S. and develops several analytic models to explain the multimodal traveler behavior in the 2017 NHTS. The third question examines the potential impacts of TNCs on transit demand in Chicago, with a particular focus on understanding heterogeneity in the effects by employing fixed effects panel regression models. By investigating various travel behavior around transit station areas, this dissertation provides insights on how TODs can be better implemented to promote sustainable and multimodal travel behavior.

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Has the COVID-19 Pandemic Changed People’s Attitude about Where to Live? Some Preliminary Answers from a Study of the Atlanta Housing Market

2021-05-04 , Kim, Ilsu

In March 2020, the national lockdowns and social distancing mandates to contain the COVID-19 pandemic in the US abruptly disrupted all aspects of urban life, requiring people to conduct daily activities including work, shopping, learning, schooling, and socializing, from home using online tools. These lockdowns and stay-at-home orders sharply increased unemployment and hindered active transactions in the housing market in the second quarter of 2020 (Liu & Su, 2021). While the high unemployment rate was a severe economic and social concern affecting housing demand, monetary easing and low interest rates increased liquidity and the flow of money into the housing market (Zhao, 2020). A growing body of work started to examine the overall vitality of the housing market in response to the disruptions caused by the pandemic (D’Lima et al., 2020; Liu & Su, 2021; Yoruk, 2020; Zhao, 2020). In addition, reports in popular media have highlighted trends in cities like New York and San Francisco, where many households were giving up expensive central city residences for low-density suburban houses with large yards. This finding implied that cities were losing their appeal given the reduction in the need for commuting in a work-from-home culture and the desire for security and open space in a low-density environment in the suburbs. Despite this type of anecdotal evidence, we know very little about how the preferences for housing in different locations are changing in response to the COVID-19 pandemic. This study explores whether and how the pandemic affected the housing preferences in the Atlanta single-family housing market. The focus goes to locational characteristics such as the accessibility to the rail transit system, accessibility to freeway systems, and walkability. The housing market participants’ attitudes toward the different travel modes can be revealed with the price effects of the accessibility-related locational characteristics. The impact of whether a house is in the inner city, inner-ring suburb, or outer-ring suburb on housing prices is also examined. A few main findings are derived from comparing the descriptive statistics and hedonic price models for 2018, 2019, and 2020. First, a steep drop in the number of transactions in the second quarter of 2020 was followed by an increase in the number of transactions and housing prices. The observed boom in the Atlanta single-family housing market aligns with the arguments of Zhao (2020) and Liu and Su (2021) that the lowered mortgage rate caused the influx of money to the housing markets across the US. Second, the positive price effect of parcel size and a pool increased in 2020 while that of square footage decreased. Third, the recently increasing preference for the inner city over the suburban area was restrained in 2020, which might have resulted from the diminished advantage of staying near the city center for job accessibility. Fourth, the pandemic did not substantially change the capitalization effect of the accessibility to a MARTA rail station and freeway. A few suggestions are made for future studies. First, the endeavor to further clarify the underlying reasons for the observations from this study would be necessary, which hedonic price models alone cannot do. Conducting a customized survey is one way to reveal the existence of and reasons for the changes in the attitudes, lifestyle, and travel patterns of diverse market participants covering both the supply and demand sides. Second, investigating the parts of the housing market that are not examined in this study will bring a comprehensive and detailed understanding of the housing market and the changes the market went through. The houses for rent and the houses other than detached single-family houses are not included in this study. Moreover, the transactions of the newly constructed houses are not usually in the FMLS data even though they take up a significant proportion of the transactions in the Atlanta region. Third, the analyses with some submarket segmentation using such criteria as the housing price, number of rooms, and location are expected to bring useful policy implications enabling detailed and customized solutions to the issues that planners are tackling.

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The effect of compact development on travel behavior, energy consumption and GHG emissions in Phoenix metropolitan area

2013-04-10 , Zhang, Wenwen

Suburban growth in the U.S. urban regions has been defined by large subdivisions of single-family detached units. This growth is made possible by the mobility supported by automobiles and an extensive highway network. These dispersed and highly automobile-dependent developments have generated a large body of work examining the socioeconomic and environmental impacts of suburban growth on cities. The particular debate that this study addresses is whether suburban residents are more energy intensive in their travel behavior than central city residents. If indeed suburban residents have needs that are not satisfied by the amenities around them, they may be traveling farther to access such services. However, if suburbs are becoming like cities with a wide range of services and amenities, travel might be contained and no different from the travel behavior of residents in central areas. This paper will compare the effects of long term suburban growth on travel behavior, energy consumption, and GHG emissions through a case study of neighborhoods in central Phoenix and the city of Gilbert, both in the Phoenix metropolitan region. Motorized travel patterns in these study areas will be generated using 2001 and 2009 National Household Travel Survey (NHTS) data by developing a four-step transportation demand model in TransCAD. Energy consumption and GHG emissions, including both Carbon Dioxide (CO₂) and Nitrous Oxide (N₂O) for each study area will be estimated based on the corresponding trip distribution results. The final normalized outcomes will not only be compared spatially between Phoenix and Gilbert within the same year, but also temporally between years 2001 and 2009 to determine how the differential land use changes in those places influenced travel. The results from this study reveal that suburban growth does have an impact on people's travel behaviors. As suburbs grew and diversified, the difference in travel behavior between people living in suburban and urban areas became smaller. In the case of shopping trips the average length of trips for suburban residents in 2009 was slightly shorter than that for central city residents. This convergence was substantially due to the faster growth in trip lengths for central city compared to suburban residents in the 8-year period. However, suburban residents continue to be more energy intensive in their travel behavior, as the effect of reduction in trip length is likely to be offset by the more intensive growth in trip frequency. Additionally, overall energy consumption has grown significantly in both study areas over the period of study.

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