NTL Record

Title Estimating Spatial Travel Times Using Automatic Vehicle Identification Data
Record ID 23531
Personal Name
Creator
Dion, Francois; Rakha, Hesham
Corporate
Contributor
Virginia Polytechnic Institute and State University. Transportation Institute; Virginia. Dept. of Transportation; National ITS Implementation Research Center (Va.)
Publisher Virginia. Department of Transportation
Publication Date 20010000
Language English
Abstract 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.
Rosap ID dot:5457
Rosap URL https://rosap.ntl.bts.gov/view/dot/5457
TRT Terms Advanced traveler information systems; Travel time; Algorithms; Automatic vehicle identification; Validity; Estimating; Real time information
General Subjects Traffic conditions
Classification NTL - INTELLIGENT TRANSPORTATION SYSTEMS - INTELLIGENT TRANSPORTATION SYSTEMS
Geographical
Coverage
United States
Resource type Research Paper
URL https://ntlrepository.blob.core.windows.net/lib/23000/23500/23531/AVI-Filter-Paper-TRB-2003-Submittal-Revised.pdf
Format PDF
Database NTL Digital Repository