Incorporation of Speed/Travel-Time Data Sets in Traffic Performance Analysis

Details

• Creators:
  Refai, Hazem H. ; Ahmed, Samir ; Bitar, Naim ; Kaleia, Mohanad ; Mostahinic, Nika ; Alamiri, Tamer ; Gupta, Varun
• Corporate Creators:
  University of Oklahoma. School of Electrical and Computer Engineering
• Corporate Contributors:
  Oklahoma. Department of Transportation. Office of Research and Implementation ; Southern Plains Transportation Center ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Algorithms
  • Bayes' theorem
  • Bluetooth technology
  • Data collection
  • Neural networks
  • Real time information
  • Speed data
  • Traffic incidents
  • Traffic speed
  • Traffic surveillance
  More +
• Publication/ Report Number:
  STPC 15.2 -08
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final report, Jan 2016 - Jan 2019
• Corporate Publisher:
  Southern Plains Transportation Center
• Description:
  An accurate Travel Time (TT) information is essential for traffic prediction and analysis. Correct TT measurements can be used to reduce congestions, improve safety and enhance traffic flow. The work detailed in this paper reports on the development and implementation of an inexpensive Bluetooth traffic monitoring system for reliable and real-time TT measurements. The Bluetooth system proved instant and accurate TT measurements 99.9% of the time. Furthermore, algorithms used for collecting traffic information from various ODOT platforms were fully developed, integrated, and evaluated. National Performance Management Research Dataset (NPRMDS) was chosen for developing TT models, and for identifying TT outliers and anomalies. Since incidents on highways increase TT, artificial neural network (ANN) model was designed for incident classification based on many features, such as vehicle count, weather condition and traffic flow. The ANN model reported accuracy of 91%. Moreover, a Bayesian model for detecting non-recurrent congestions was developed and evaluated.
• Format:
  PDF
• Funding:
  STPC 15.2 -08
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/55579/dot_55579_DS1.pdf
• File Type:
  [PDF - 7.68 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:eb24a305a3c1b0b459d062f54052b0091784bd4aca8eb1450e3c58c7e52e88194a73f712a2d88ebc3389cd6a34a26d32b6905f3b6def0f77fa5028a68ee47f61