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- W1555914449 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" @default.
- W1555914449 created "2016-06-24" @default.
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- W1555914449 date "2003-01-01" @default.
- W1555914449 modified "2023-09-23" @default.
- W1555914449 title "Estimating spatial travel times using automatic vehicle identification data" @default.
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