rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Making every day count
    sub title: applying data-driven safety analyses in a TxDOT district
  title info:
    title: Data-Driven Safety Analysis (DDSA) framework for the Beaumont district
  name:
    name part: Wunderlich, Robert
    name part: (Research engineer)
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Dixon, Karen
    role:
      role term: author.
  name:
    name part: Wu, Lingtao
    role:
      role term: author.
  name:
    name part: Geedipally, Srinivas Reddy
    role:
      role term: author.
  name:
    name part: Dadashova, Bahar
    role:
      role term: author.
  name:
    name part: Shipp, Eva
    role:
      role term: author.
  name:
    name part: Texas
    name part: Department of Transportation.
    name part: Research and Technology Implementation Office,
    role:
      role term: sponsoring body.
  name:
    name part: United States
    name part: Federal Highway Administration,
    role:
      role term: sponsoring body.
  name:
    name part: Texas A & M Transportation Institute
    role:
      role term: publisher.
  type of resource: text
  genre: bibliography
  genre: Technical reports.
  origin info:
    place:
      place term: txu
    date issued: 2020
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvi, 274 pages) : color illustrations
  abstract: Using a data-driven approach to analyze safety issues and projects will help Texas Department of Transportation (TxDOT) districts to target safety investments with more confidence and reduce crashes on Texas highways. Many predictive and systemic analysis tools are now available that provide the means to quantify safety impacts in a similar way so that roadway capacity and operations, environmental impacts, drainage, and pavement life can be quantified. The Texas A&M Transportation Institute developed a logical, practical, and data-driven framework for integrating these tools into practice within the TxDOT Beaumont District. There are four basic elements to consider when building a data-driven framework. The first element is the description of traffic safety issues. The second is the identification of roadway segments and intersections where the greatest potential to reduce crashes exists and the development and evaluation of potential safety treatments. This identification includes the assessment of historic crash trends combined with the application of new but proven safety analysis methods. The source of this information was TxDOT's Crash Record Information System, maintained by TxDOT's Traffic Operations Division. The third element is quantifying the correlation of prevalent crash types with specific roadway features to allow the development and evaluation of systemic safety improvements. The fourth element is the integration of safety assessment directly into the project development process or overall process from the conceptual to the construction phase. The purpose of this effort is to identify ways to better integrate safety assessment into identifying safety projects and to build more safety into new construction, reconstruction, and maintenance activities. The framework is intended to be a model that can be adapted and utilized in other TxDOT districts to assist decision makers as they determine viable roadway safety investments.
  note: by Robert Wunderlich, P.E., Senior Research Engineer and Director, Center for Transportation Safety, Karen Dixon, Ph.D., P.E., Senior Research Engineer and Division Head,Traffic Operations and Roadway Safety Division, Lingtao Wu, Ph.D., Assistant Research Scientist, Center for Transportation Safety, Srinivas Geedipally, Ph.D.,, P.E., Associate Research Engineer, Center for Transportation Safety, Bahar Dadashova, Ph.D,. Associate Transportation Researcher, Traffic Operations and Roadway Safety Division and Eva Shipp, Ph.D., Research Scientist, Center for Transportation Safety.
  note: Open access content Open access content star
  note: Implementation report: Sept 2017-Aug 2019.
  note: Performed in cooperation with the Texas Department of Transportation and the Federal Highway Administration 5-9052-01.
  note: Includes bibliographical references (pages 273-274).
  subject:
    geographic code: n-us-tx
  subject:
    topic: Traffic safety
    geographic: Texas
    topic: Evaluation
    topic: Data processing
  subject:
    topic: Traffic accidents
    geographic: Texas
    topic: Data processing
  subject:
    topic: Traffic safety
    geographic: Texas
    topic: Planning
  subject:
    topic: Traffic accidents
    geographic: Texas
    topic: Management
  subject:
    topic: Predictive models
  subject:
    topic: Crash analysis
  subject:
    topic: Crash data
  subject:
    topic: Crash rates
  subject:
    topic: Safety analysis
  related item:
    title info:
      title: Research report (Austin, Tex.) ; no. 5-9052-01-R1
  identifier: http://tti.tamu.edu/documents/5-9052-01-R1.pdf
  identifier: http://tti.tamu.edu/documents/5-9052-01-PSR.pdf
  related item:
    location:
      url: http://tti.tamu.edu/documents/5-9052-01-PSR.pdf
  access condition: Open access content
  record info:
    record content source: NATTR
    record creation date: 231024
    record change date: 20231117194230.8
    record identifier: in00004752822
    language of cataloging:
      language term: eng