UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

Browse

Filters

2007 - 20102

Settings

Subject: search.filters.subject.discrete choice model

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    MODELING CAR OWNERSHIP, TYPE AND USAGE FOR THE STATE OF MARYLAND
    (2010) Liu, Yangwen; Cirillo, Cinzia; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Over the last few decades there has been a great increase in the number of cars in the United States. Given the importance of vehicle ownership on both transport and land-use planning and its relationship with energy consumption, the environment and health, the growth in the number of vehicles and their use has been one of the most intensely researched transport topics over many years. This thesis presents a car ownership model framework for the State of Maryland. The model has been calibrated on publicly available data (2001 and 2009 National Household Travel Survey) without the burden and the consequent cost of collecting additional data. The sample has been sufficient to correctly estimate a number of relevant socio demographic and land use variables. The model has then been applied, for demonstration purposes, to test a number of sensitivity analysis concerning changes in housing density, income, urbanization, unemployment rates and fuel price.
  • Thumbnail Image
    Item
    Empirical analysis and modeling of freeway incident duration
    (2007-12-14) Kim, Woon; Chang, Gang-Len; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This study presents a set of models for predicting incident duration and identifying variables associated with the incident duration in the state of Maryland. The incident database for years 2003 to 2005 from the Maryland State Highway (MDSHA) database is used for model development, and year 2006 for the model validation. This study, based on the preliminary analysis with the Classification Tree method, has employed the Rule-Based Tree Model to develop the primary prediction model. To enhance the prediction accuracy for some incidents with complex nature or limited samples, the study has also proposed and calibrated several supplemental components based on the Multinomial Logit and Regression methods. Although the prediction accuracy could still be improved if a data set with better quality is available, the developed set of models offers an effective tool for responsible agencies to estimate the approximate duration of a detected incident, which is crucial in projecting the potential impacts on the highway network.