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mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Temporal variations in daily traffic flow profiles on urban access-controlled roadways
  name:
    name part: Knapp, Keith Kendall.
    role:
      role term: creator
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: xx
    date issued: 1997
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xiii, 283 leaves : illustrations ; 28 cm.
  abstract: The proper evaluation of transportation improvements requires
  abstract: the estimation of daily traffic flow profiles. This research
  abstract: investigated the temporal variations of daily traffic flow
  abstract: profiles on urban access-controlled roadways. A daily
  abstract: traffic flow profile modeling procedure was developed.
  abstract: Hourly traffic flow data and study site characteristics were
  abstract: obtained for 42 locations in Texas. This information was
  abstract: gathered for as many years as possible between 1969 and 1995
  abstract: and daily traffic flow profiles were calculated. The study
  abstract: site characteristics of interest included: annual average
  abstract: daily traffic (AADT) per lane, county population, roadway
  abstract: orientation, and location. Daily traffic flow profiles on
  abstract: urban access-controlled roadways typically have four
  abstract: intervals. The consistent definition of these intervals
  abstract: allows their attributes to be modeled. Twelve straight-line
  abstract: approximations of each daily traffic flow profile were
  abstract: completed. The best-fit approximation approach defined peak
  abstract: period attributes with the hours that had volumes within 25
  abstract: percent of their most appropriate peak-hour volume.
  abstract: Transitions between the peak and off-peak periods were one or
  abstract: two hours wide. The defining attributes of the straight-line
  abstract: approximations were modeled. AADT per lane was the focus of
  abstract: these models. Peak-period durations were modeled with
  abstract: respect to AADT per lane, and the morning peak-period start
  abstract: hour and evening peak-period end hour were based on peak-
  abstract: period duration. Interval magnitudes were related to
  abstract: interval duration or the database average. A seven-step
  abstract: procedure was developed that combined the model results for
  abstract: an estimation of daily traffic flow profiles. The validity
  abstract: of the profile attribute models was tested. It was found
  abstract: that the majority of the models estimated their straight-line
  abstract: approximation counterparts relatively well. Most of the
  abstract: average interval durations and magnitudes were not
  abstract: significantly different than those originally approximated.
  abstract: The results of the proposed approach were compared to those
  abstract: of the current profile approximation methodology and the
  abstract: calculated daily traffic flow profiles at 15 validation study
  abstract: sites. The current approach approximated daily traffic flow
  abstract: profiles more accurately than the proposed approach. The
  abstract: gross nature of the straight-line process within the proposed
  abstract: approach overwhelms the advantages it offers and the
  abstract: estimation abilities of the individual profile attribute
  abstract: models developed.
  note: by Keith Kendall Knapp.
  note: Vita.
  note: "Major Subject: Civil Engineering".
  note: Issued also on microfiche from University Microfilms Inc.
  note: Includes bibliographical references: pages 147-149.
  note: Ph. D. Texas A&M University 1997.
  subject:
    topic: Major civil engineering
  identifier: 98-15776 UMI
  identifier: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  record info:
    record content source: TXA
    record creation date: 980720
    record change date: 20190325093354.0
    record identifier: in00001424425