National Center for Smart Growth Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/21473

The National Center for Smart Growth (NCSG) works to advance the notion that research, collaboration, engagement and thoughtful policy development hold the key to a smarter and more sustainable approach to urban and regional development. NCSG is based at the University of Maryland, College Park, housed under the School of Architecture, Planning, and Preservation, with support from the College of Agriculture & Natural Resources, the A. James Clark School of Engineering, the School of Public Policy, and the Office of the Provost.

Browse

Start date: 2010End date: 2016

Search Results

Now showing 1 - 10 of 27
  • Thumbnail Image
    Item
    Gradual Rasterization: Redefining the Spatial Resolution in Transport Modeling
    (2014) Moeckel, Rolf; Donnelly, Rick
    Finding the appropriate spatial resolution in modeling is a serious challenge at the beginning of every modeling project. The paper presents a methodology to adjust the spatial geography to the resolution of a network. Based on the quadtree algorithm, raster cells are generated that are dynamic in size. Smaller raster cells are used in urban areas and larger raster cells are used in low-density, rural areas. Trip tables of a travel demand model for the State of Georgia are disaggregated to this new zone system of raster cells, and assignment results validate significantly better than when using the original zone system.
  • Thumbnail Image
    Item
    Comparing Driver and Capacity Characteristics at Intersections With and Without Red Light Cameras
    (2011) Weldegiorgis, Yohannes; Mishra, Sabyasachee; Jha, Manoj K.
    The primary purpose of installing Red Light Cameras (RLCs) is to improve intersection safety by discouraging motorists to cross the intersection when the signal for approaching vehicles turns red. Due to the fear of being fined when crossing an RLC equipped intersection at the onset of the red signal, many approaching vehicles may have a tendency of stopping during the yellow phase. This tendency may impact intersection capacity, which can be significant in congested transportation networks during rush hours, especially when several intersections are equipped with RLCs along a sequence of traffic signals, resulting in a disruption of traffic progression. In order to examine the driver and capacity characteristics at intersections with RLCs and compare them with those without RLCs we develop a binary probit choice model to understand driver's stop and go behavior at the onset of yellow intervals, also known as dilemma zone. Further, in order to capture the impact to intersection capacity at intersections with RLCs we develop a probabilistic computational procedure using data from ten intersection pairs (with and without RLCs) in the Baltimore area. The results indicate that, in general, RLCs reduce the intersection capacity since driver's travel behavior is influenced by the presence of the cameras. Other contributory factors for the so-called capacity reduction, such as driver population (e.g., familiar vs. unfamiliar drivers) and traffic-mix (e.g., trucks vs. passenger cars) characteristics have been left for future works.
  • Thumbnail Image
    Item
    A Case for Increased State Role in Transit Planning: Analyzing Land Use and Transit Ridership Connections Using Scenarios
    (2011) Chakraborty, Arnab; Mishra, Sabyasachee
    Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, we develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state. We then discuss its implications for regional and state-level decision-making. We chose the state of Maryland as our study area. Using a number of criteria, we subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. We estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. We find that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. We also find that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next we used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. We use the resulting scenarios to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.
  • Thumbnail Image
    Item
    Examination of Regional Transit Service Under Contracting: A Case Study in the Greater New Orleans Region
    (Mineta Transportation Institute (MTI), 2011) Iseki, Hiroyuki
    Many local governments and transit agencies in the United States face financial difficulties in providing adequate public transit service in individual systems, and in providing sufficient regional coordination to accommodate transit trips involving at least one transfer between systems. These difficulties can be attributed to the recent economic downturn, continuing withdrawal of the state and federal funds that help support local transit service, a decline in local funding for transit service in inner cities due to ongoing suburbanization, and a distribution of resources that responds to geographic equity without addressing service needs. This study examines two main research questions: (1) the effect of a “delegated management” contract on efficiency and effectiveness within a single transit system, and (2) the effects of a single private firm—contracted separately by more than one agency in the same region—on regional coordination, exploring the case in Greater New Orleans. The current situation in New Orleans exhibits two unique transit service conditions. First, New Orleans Regional Transit Authority (RTA) executed a “delegated management” contract with a multinational private firm, outsourcing more functions (e.g., management, planning, funding) to the contractor than has been typical in the U.S. Second, as the same contractor has also been contracted by another transit agency in an adjacent jurisdiction—Jefferson Transit (JeT), this firm may potentially have economic incentives to improve regional coordination, in order to increase the productivity and effectiveness of its own transit service provision. Although the limited amount of available operation and financial data has prevented us from drawing more definitive conclusions, the findings of this multifaceted study should provide valuable information on a transit service contracting approach new to the U.S.: delegated management. This study also identified a coherent set of indices with which to evaluate the regional coordination of transit service, the present status of coordination among U.S. transit agencies, and barriers that need to be resolved for regional transit coordination to be successful.
  • Thumbnail Image
    Item
    Hotspots for Growth: Land Use Change and Priority Funding Area Policy in a Transitional County in the U.S.
    (2010) Hanlon, Bernadette; Howland, Marie; McGuire, Michael
    This paper uses a logit model to estimate whether and to what extent Maryland’s Priority Funding Area (PFA) program steers urban growth to locations inside targeted growth area boundaries of an ex-urban county in the outer suburbs of the Washington, D.C. region. The results of our model indicate that the size of an agricultural parcel, its distance from urban parcels, its proximity to highways, the quality of the land for agriculture, and the location in or outside of PFAs influence the probability an agricultural parcel will remain in agriculture or be converted to urban use. We find that some of the areas experiencing the greatest market pressure for development are located outside PFAs and, although Maryland’s incentive-based strategy reduces the likelihood a parcel outside a PFA will transition to urban use, this policy is not one hundred percent effective.
  • Thumbnail Image
    Item
    A Joint Travel Demand and Environmental Model To Incorporate Emission Pricing For Large Transportation Networks
    (2012) Mishra, Sabyasachee; Welch, Timothy; Welch
    Emission reduction strategies are gaining greater attention to support the national objective for a sustainable and green transportation system. A large percent of emission contribution that arises from transportation modes are primarily from auto and truck travel. Reductions in highway travel require prudent planning strategies and modeling user’s response to planner’s policies. Modeling planning goals and user’s response is a challenging task. In this paper the authors present a joint travel demand and environmental model to incorporate vehicle emission pricing (VEP) as a strategy for emission reduction. First, the travel demand model determines the destination, mode and route choice of the users in response to the VEP strategy set by the planner. Second, the emission model provides NOx, VOC, and CO2 estimates at a very detailed level. A Base-case and three models are proposed to incorporate VEP in a multimodal transportation network. The objective function of the Base-case is the minimization of Total System Travel Time (TST), and the models are designed with the objective of minimizing Total System Emission (TSE). User Equilibrium method is used for travel to model user responses and solved by Frank Wolfe algorithm. The Base-case represents “do-nothing” conditions and the three models address the interactions between planner’s perspectives and user responses to VEP strategies. The proposed model is applied to Montgomery County’s (located in the Washington DC-Baltimore region) multimodal transportation network. The case study results show that VEP can be used as a tool for emission reduction in transportation planning and policy.
  • Thumbnail Image
    Item
    The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis
    (2014) Liu, Chao; Ding, Chuan; Lin, Yaoyu; Wang, Yaowu
    The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process.
  • Thumbnail Image
    Item
    Thinking Outside the Bus
    (2012) Iseki, Hiroyuki; Smart, Michael; Yoh, Allison; Taylor, Brian D.
    This is a short, accessible article that provides a synopsis of findings from the research titled “Tool Development to Evaluate the Performance of Intermodal Connectivity (EPIC)” in collaboration with UCLA Institute of Transportation Studies. This research has examined various factors that can substantially influence transit users’ perception of service quality at bus stops and trains stations, and also what factors transit managers think important to improve customers' satisfaction. Recently, the project has developed a tool for transit agencies to identify service quality improvements at transit facilities, which has been presented in the American Planning Association (APA) National Planning Conference in Los Angeles, April, 2012. Publications related to this research are listed under " FURTHER READING" on page 15.
  • Thumbnail Image
    Item
    A Multiobjective Optimization Approach to Smart Growth in Land Development
    (2010) Faria, Jose; Gabriel, Steven; Moglen, Glenn
    In this paper we describe a multiobjective optimization model of "Smart Growth" applied to land development in Montgomery County, Maryland. The term "Smart Growth" is generally meant to describe those land development strategies which do not result in urban sprawl, however the term is somewhat open to interpretation. The multiobjective aspects arise when considering the conflicting interests of the various stakeholders involved: the government planner, the environmentalist, the conservationist, and the land developer. We present a formulation, which employs linear and convex quadratic objective functions for the stakeholders that are subject to polyhedral and binary constraints. As such, the resulting optimization problems are convex, quadratic mixed integer programs which are known to be NP-complete (Mansini and Speranza, 1999). We report numerical results with this model and present these results using a geographic information system (GIS).
  • Thumbnail Image
    Item
    The Contagion Effect of Neighboring Foreclosures on Own Foreclosures
    (2010) Lawley, Chad; Towe, Charles
    In this paper, we examine a highly localized contagion effect of foreclosures and find strong evidence that social interactions influence the decision to foreclose. We utilize a hazard model and a unique spatially explicit dataset documenting parcel level residential foreclosures in Maryland for the years 2006 through 2009. We combine these data with tax and assessment data, loan data, Census, and unemployment data. These data allow us to control for important factors influencing the likelihood of foreclosure within a given community, including the prevalence of subprime loans and the distribution of socioeconomic characteristics. Additionally, we use the tax data to construct variables describing individual homes, surrounding homes, and community. These variables include structural characteristics of houses, their price history, and length of ownership.