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    A Comprehensive Review Of Motorcycle Crashes In Maryland

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    Mazloomdoust_morgan_0755M_10181.pdf (1.290Mb)
    Permanent Link
    http://hdl.handle.net/11603/10361
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    • MSU Student Collection
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    Author/Creator
    Mazloomdoust, Gholamhossein
    Date
    2011
    Type of Work
    Text
    theses
    Department
    Transportation
    Program
    Master of Science
    Rights
    This item is made available by Morgan State University for personal, educational, and research purposes in accordance with Title 17 of the U.S. Copyright Law. Other uses may require permission from the copyright owner.
    Subjects
    Transportation
    City planning
    Abstract
    This study identifies the recurring or common road characteristics of motorcycle crashes in Maryland from 1998 to 2007. Motorcycle crash data was obtained from the National Highway Traffic Safety Administration's Crash Outcome Data Evaluation System (CODES), and road inventory data was obtained from the Maryland State Highway Administration. Both sets of data were integrated, and fault tree analysis and variable selection methods were utilized to find the highest frequency crash cases. In order to specify the minimum number of variables that explain most of the observed variance, a categorical principal component analysis was employed. In addition, ordinal logistic models were developed to estimate the number of motorcycle crashes for road segments within each road class. The logistic ordinal regression analysis results show that area type, median type, speed limit, average annual daily traffic (AADT), international roughness index (IRI), and number of through lanes affect the number of motorcycle crashes on Maryland's road segments. Interestingly, government control and shoulder type appear to have no significant impact on the number of motorcycle crashes. The developed ordinal logistic model can also be used to calculate the number of motorcycle crashes for each road characteristic. SHA engineers and safety officials can use this study's results to develop solutions for identified safety deficiencies.


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    Growing the Future, Leading the World!


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.