Development of statistical models to forecast crossing times of commercial vehicles.

Details

• Creators:
  Kang, Dong Hun ; Ochoa, Cesar ; Rajbhandari, Rajat ; Garcia, Francisco
• Corporate Creators:
  Texas Transportation Institute. University Transportation Center for Mobility
• Corporate Contributors:
  United States. Department of Transportation. Research and Innovative Technology Administration ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • International borders
  • Truck traffic
  • Traffic counts
  • Traffic measurement
  • Travel time
  • Commercial vehicles
  • United States-Mexico border, Truck crossing times, Real time information, Travel time, Radio frequency
  • identification, Commercial vehicles, Research projects
• Publication/ Report Number:
  UTCM Project #10-09-60
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas
• Corporate Publisher:
  University Transportation Centers Program (U.S.)
• Abstract:
  Border crossing time measurement systems for commercial vehicles are being implemented throughout ; the U.S.-Mexico border. These systems are based on radio frequency identification (RFID) technology. ; With funding from the Federal Highway Administration, the Texas Transportation Institute (TTI)/Battelle ; team installed an RFID-based system at the Bridge of the Americas (BOTA) in El Paso, Texas, to measure ; and archive crossing times of commercial vehicles. The RFID system at BOTA is already operational, and ; current truck crossing time information is relayed and archived in a centralized repository. In addition, with ; funding from the Texas Department of Transportation, TTI deployed RFID systems on the Pharr-Reynosa ; Bridge. These systems measure the current crossing time and provide the information to users; however, ; there is no system in place to predict the crossing times of trucks. In fact, there are no systems in place at ; the U.S.-Mexico border to predict traffic conditions including crossing times of trucks. In this project, ; statistical models were developed to predict crossing times of trucks over a short range of time. The ; statistical prediction models use historic data and take into account empirical relationships between ; border-crossing-related parameters and truck crossing times.
  More +
• Format:
  PDF
• Funding:
  DOT Grant No. DTRT06-G-0044
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/23232/dot_23232_DS1.pdf
• File Type:
  [PDF - 1.29 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:1b1bdd354d94720df996ea47ffeb768d6b55bc200b989e35fe7a67b8876868ab54b1f2d24feadb54bf27164f25b5722d55a8942a642529f76e8badbfadd39a39