Improving the Efficiency and Accuracy of ODOT Temporary Traffic Monitoring System

Details

• Creators:
  Kaja Najumudeen, Mohamat Eirban Ali Bin ; Kaleia, Muhanad Shab ; Refai, Hazem H.
• Corporate Creators:
  University of Oklahoma. School of Electrical and Computer Engineering
• Corporate Contributors:
  Oklahoma. Department of Transportation. Office of Research and Implementation
• Subject/TRT Terms:
  • Traffic
  • Vehicle classification
  • Traffic data
  • Automation
  • Freeway management systems
  • Freeway operations
  • Freeways
  • Technology
  • Intelligent transportation systems
  • Temporary traffic monitoring system
• Publication/ Report Number:
  FHWA-OK-19-02
• Resource Type:
  Tech Report
• Geographical Coverage:
  Oklahoma ; United States
• Edition:
  Final Report, Oct 2018 – Sept 2019
• Corporate Publisher:
  Oklahoma. Department of Transportation
• Abstract:
  Vehicle detection, counting, and classification are key for not only improving road designs and maintenance, but also driver safety. In pursuit of these objectives, the authors proposed an automated system for collecting temporary vehicle data (e.g., count, speed, vehicle classification based on axles, collection date and time, among other factors). The framework is composed of three main components: 1) an inexpensive portable sensor for counting and classifying vehicles; 2) an Android app to easily calibrate the sensor on-site and fetch collected sensor data; and 3) a server that leverages wireless communication and cloud technology for processing and presenting data. A first-phase system was deployed and tested by Oklahoma Department of Transportation. A project extension further developed and debugged the system and validated functionality. The two-year extension includes server maintenance and support for the Traffic Counting and Monitoring System web service and android application
• Format:
  PDF
• Funding:
  ODOT SPR Item Number 2301
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/57424/dot_57424_DS1.pdf
• File Type:
  [PDF - 4.31 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:0e1ecb6d6775d56b6dc8a1066734c4c2baa74785900e2db2baa5f2b294ee9937