Urban and Regional Planning and Design Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/26355

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Start date: 2010Subject: search.filters.subject.Transportation

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    Planning towards an equitable sharing economy: On housing, on transportation, on policymaking
    (2021) Zou, Zhenpeng; Knaap, Gerrit; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The sharing economy has experienced phenomenal growth in the past decade. Its two most popular sectors, short-term rental (STR) and shared mobility, have significantly transformed people’s travel behavior and disrupted the urban housing/transportation markets. On the other hand, planning and policy efforts lag behind the growth of the sharing economy due to its novelty and its market-based business model. In this dissertation, I use three empirical studies to demonstrate one of those planning and policymaking challenges from the equity perspective. In the first study, I investigate the impact of STR on single-family housing prices in Washington DC using a data-driven, hedonic analytical framework. Not only do I find a significant price inflation as a result of increasing STR activities, but I also identify the spatially uneven impacts that can adversely affect housing affordability in some minority-populated neighborhoods in the city. In the second study, I focus on the built and social environment factors to explain the spatial distribution of e-scooter sharing trips on Washington DC’s streets. Using real-time, trip trajectory level data, I am able to examine not only the built environment factors for a trip’s origin and destination neighborhoods, but also the street design factors for a trip’s traversing paths. Moreover, I apply a machine-learning based clustering analysis to segment trips by their temporal patterns, built environment, and social environment attributes. With both data-intensive analyses, I identify potential equity issues and opportunities associated with the emerging e-scooter sharing in DC. In the third study, I expand my analysis on STR and shared micromobility in a cross-city, cross-section exploration. I find similar tourist-oriented spatial patterns for three types of activities, including STR, station-based bike-sharing, and dockless bike/e-scooter sharing. Additionally, I find a significant lag in their uses in socially disadvantaged neighborhoods in eight cities, as well as identifying a potential connection between active STR business and gentrification in communities of high social vulnerability. The policy heterogeneities within the eight cities provide different angles to understand the feasible and effective planning practices and policy approaches to address the equity concerns on the rising sharing economy.
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    Housing Value and Light Rail Transit Construction: Evidence from Three Essays
    (2020) Peng, Qiong; Knaap, Gerrit Jan; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In three essays, this dissertation explores what’s the determinants of multifamily rents and whether an anticipated investment in light rail transit influences multifamily rents and single-family housing prices in the rail transit pre-service period. In the first essay, I applied a multilevel linear model approach to account for the multifamily housing hierarchical data structure, and assessed the effects of service provision and management on multifamily rents. The findings show that pet allowance, availability of a short-term lease, and storage service increase rents significantly, while general renovations and availability of services for those with disabilities do not increase rents. The second essay empirically tests whether light rail transit in the pre-service period impacts multifamily housing rent in the transit corridor. Two approaches, a first-difference method and a difference-in-difference method, are used to test the research question. The results indicate that the rents of two-bedroom, three-bedroom, and four-bedroom units within a half-mile from planned light rail stops have significantly increased from 2015 to 2018 compared with the rent of units in other areas in Montgomery County. The third essay examines the temporal and spatial variation of the effect of the Purple Line on single-family home prices during the rail line pre-service period. The results show that the housing market saw a premium in 2012, the year the Purple Line project progressed into the preliminary engineering phase. The results also show that the effect of the new light rail transit line is distributed unevenly across the catchment areas of newly built stations and established stations.
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    THREE ESSAYS ON URBAN TRANSPORTATION STUDIES IN WASHINGTON D.C.: SAFETY EFFECT OF ALL-WAY STOP CONTROL, SAFETY EFFECT OF REVERSIBLE LANE AND LOADING ZONE ALLOCATION
    (2019) Deng, Zuxuan; Knaap, Gerrit-Jan; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Systematic data-driven and evidence-based urban transportation policy making and evaluation become increasingly important for public agencies to ensure transparent and efficient services. This dissertation, consisting of three essays on urban transportation studies, focuses on two issues (safety and asset management) that are broadly related with urban transportation policy making and evaluation in Washington D.C. In Chapter One, I evaluate the safety effect of All Way Stop Control (AWSC) conversion with an observational treatment group and a randomly selected control group from stratified samples. Selection bias and time trend are controlled using empirical strategies such as Multiway ANOVA and Difference-in-Differences analysis. The study reveals statistically significant reductions of right angle crashes upon AWSC conversions. However, for all the other collision types, including right turn, left turn, rear end, sideswipes and bicycle crashes, none of the estimated coefficients were statistically significant. In addition, the study quantified a statistically significant increase of straight hit pedestrian crashes upon AWSC conversion. In Chapter Two, I study the safety effect of removing reversible lane operations along urban arterials. Taking advantage of the termination of three reversible lane arterials in 2010, the evaluation is performed using the Before-After (BA) study with a control group and the Empirical Bayes (EB) method, respectively. I estimate Crash Modification Factors (CMF) for all crashes, fatal/injury crashes, property damage only (PDO) crashes, rear-end crashes, left turn crashes and sideswipe crashes. My findings suggest a clear tradeoff between safety and the gain of peak direction capacity by operating reversible lanes along urban arterials. In Chapter Three, I propose an innovative procedure for allocating scarce curbside space for loading zones in an equitable, quantifiable and repeatable manner. Freight Trip Generation (FTG) models are used to estimate the delivery needs for business establishments at a block face level. The current numbers of loading zones per block face are regressed against the Gross FTG (GFTG) per block face and other block face characteristic variables using zero-truncated Negative Binomial models to establish a baseline. Curbside spaces are then assigned as loading zones in an iterative process.
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    A Micro-Level Examination of the Impact of Rail Transit Investments on the Patterns of Firm Dynamics
    (2018) Saeed, Basheer A.; Iseki, Hiroyuki; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Transit-oriented development has been increasingly implemented at stations of both existing and new fixed transit systems across the U.S. to stimulate local economy and create livable communities. A common belief among planners in favor of transit-oriented development is that the provision of passenger rail systems promotes urban development around rail stations. There is a lack of empirical evidence, however, that supports this presumption. To address the gap in relevant literature, this dissertation examines the impact of passenger rail stations on the four different patterns of firm dynamics in the State of Maryland—firm birth and inward relocation as positive impacts, and firm closure and outward relocation as negative impacts. This dissertation uses both standard and propensity-score-weighted negative binomial regression methods to analyze the dependent variables of firm dynamics constructed from the National Establishment Time Series (NETS) panel data of the State of Maryland from 1990 to 2010. By examining both positive and negative impacts of firm dynamics, this dissertation estimates the likelihood of firm retainment and net relocation for areas in proximity of the passenger rail stations, while controlling for a number of potentially confounding factors. Positive and statistically significant relationships are found between proximity to the passenger rail stations and the rates of firm births and inward relocating firms in Maryland, regardless of differences in the level of maturity of stations. From 1990 to 2010, the areas of passenger rail stations in Maryland experienced a wide range of rates of growth in firm density, depending on the year of station opening. The results of the four different patterns of firm dynamics suggest that areas near passenger rail stations gain belated economic benefits, well after the introduction of rail stations, shown by higher likelihood of firm retainment and net relocation around the mature rail stations opened before 1990. In comparison, areas near the less mature stations that opened after 1990 had predominantly lower likelihood of firm retainment and net firm relocation. Planners and policymakers should be proactive in directing development near rail stations by adopting a variety of measures and policies that support or at least consistent with transit-oriented development.
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    ESTIMATING THE IMPACTS OF CAPITAL BIKESHARE ON METRORAIL RIDERSHIP IN THE WASHINGTON METROPOLITAN AREA
    (2017) Ma, Ting; Knaap, Gerrit J.; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Demographic changes and shared-mobility technology have redefined the urban transportation fabric. Bike share, a public short-term bicycle rental program, has emerged around the world. Many users find bike share to be a convenient, healthy, and smart transportation option that solves first- and last-mile issues. But some are concerned that it may challenge existing rail transit systems and reduce ridership. Hence, it is important to understand the impacts of a bike share program on rail transit ridership. The Washington metropolitan area lends itself well to studying this topic. Both the bike share and rail transit systems in this area, Capital Bikeshare (CaBi) and Metrorail, are the largest in the United States. According to the Washington Metropolitan Area Transit Authority (WMATA), which operates Metrorail service, CaBi services may challenge Metrorail ridership, especially for the short-distance trips. Based on WMATA’s concern, I explore whether CaBi substitutes for Metrorail and reduces its ridership. An exploratory analysis finds evidence that CaBi can complement Metrorail trips in some cases and substitute for rail in others. To estimate CaBi’s impacts more precisely, three regression models—the Direct Ridership Model (DRM), the Difference-in-Difference (DID) model, and the Station-Specific Dummies (SSD) model—were applied. The results of the three models consistently demonstrate CaBi’s mixed impacts. CaBi may complement some Metrorail trips, but substitute for others, depending on the type and time. More importantly, the SSD results found that CaBi’s impacts vary by Metrorail station locations, whether a station is a downtown D.C. core station or a non-core station in peripheral and suburban communities. CaBi reduces core Metrorail station ridership by 4,814.4 per month for the number of AM peak exits and by 4,886.9 per month for the number of PM peak entries, but increases ridership at non-core stations by up to 2,781.2 per month, at a high statistical significance level. The finding that CaBi can complement Metrorail ridership is contrary to WMATA’s concern that a bike share program poses challenges for Metrorail. Policy suggestions are provided to help WMATA maximize the benefits of CaBi’s complementary effects.
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    Defining the Resolution of a Network for Transportation Analyses: a New Method to Improve Transportation Planning Decisions
    (2016) Cui, Yuchen; Howland, Marie; Moeckel, Rolf; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.
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    Traveler Responses to Real-Time Transit Passenger Information Systems
    (2010) Zhang, Feng; Howland, Marie; Urban and Regional Planning and Design; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In recent years, a considerable amount of money has been spent on Real-time Transit Passenger Information Systems (RTPISs), which provide timely and accurate transit information to current and potential riders to enable them to make better pre-trip and en-route decisions. Understanding traveler responses to real-time transit information is critical for designing such services and evaluating their effectiveness. To answer this question, an effort is made in this dissertation to systematically conceptualize a variety of behavioral and psychological responses travelers may undertake to real-time transit information and empirically examine the causal effects of real-time information on traveler behavior and psychology. This research takes ShuttleTrac, a newly implemented real-time bus arrival information system for UMD's Shuttle-UM service, as a case for empirical study. In Part 1 analysis, using panel datasets derived from three-waved online campus transportation surveys, fixed-effects OLS models and random-effects ordered probit models are estimated to sort out causal relations between ShuttleTrac information use and general/cumulative behavioral and psychological outcomes. In addition, a two-stage instrumental variable model was estimated to examine the potential change in habitual mode choices due to real-time transit information use. The results show that with a few months of adjustment, travelers may increase their trip-making frequency as a result of real-time transit information use, and positive psychological outcomes are more prominent in both short and longer terms. In Part 2 analyses, using the cross-sectional dataset derived from the onboard survey, OLS models and ordered logit models were estimated to examine the trip-specific psychological effects of real-time transit information. The results show that these trip-specific psychological effects of real-time transit information do exist in expected directions and they vary among user groups and in different scenarios. A finding consistent across two parts of analyses is that accuracy of information plays a greater role in determining traveler behavior and psychology than the mere presence. This research contributes to the general discussion on traveler behavior under advanced information by 1) developing an integrative conceptual framework; and 2) providing useful insights into the issue with much empirical evidences obtained with revealed-preference data and sophisticated modeling techniques.