ESTIMATING SPATIAL TRAVEL TIMES USING AUTOMATIC VEHICLE IDENTIFICATION DATA

The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, it is designed to handle both steady state (mean constant) and transient (varying mean) traffic conditions. In particular, the algorithm is able to track not only travel time fluctuations that are caused by recurring congestion, but also sudden changes in roadway travel times that may result from incident or other non-recurring events. Second, the algorithm can be successfully applied on segments with low levels of AVI penetration (less than 1 percent). The algorithm estimates link travel times using a robust data-filtering procedure that identifies valid observations within a sampling interval using a dynamically varying data validity window. The size of the data validity window varies as a function of the number of observations within the current sampling interval, the number of observations in the previous interval, the number of consecutive observations outside the current validity window limits and the travel times experienced by consecutive vehicles. Application of the algorithm to two datasets of observed travel times from the San Antonio AVI system demonstrates the validity of the proposed algorithm, and in particular, its ability to track typical and sudden travel time changes in presence of low sampling rates

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• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/5457
• Supplemental Notes:
  • Publication Date: 2003. Transportation Research Board, Washington DC. Remarks: Paper prepared for presentation at the 82nd annual meeting of the Transportation Research Board, Washington, D.C., January 2003. Format: CD ROM
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  California Department of Transportation

  1120 N Street
  Sacramento, CA  United States  95814

  University of California, Berkeley

  Department of Electrical Engineering and Computer Sciences
  Berkeley, CA  United States  94720
• Authors:
  • Dion, Francois
  • Rakha, Hesham Ahmed
• Conference:
  • Transportation Research Board 82nd Annual Meeting
  • Location: Washington DC, United States
  • Date: 2003-1-12 to 2003-1-16
• Date: 2003

Language

• English

Media Info

• Pagination: 31 p.

Subject/Index Terms

• TRT Terms: Automatic vehicle identification; Traffic estimation; Travel time

Filing Info

• Accession Number: 00941671
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH, NTL, STATEDOT
• Created Date: May 1 2003 12:00AM