Modeling Urban Link Travel Time with Inductive Loop Detector Data by Using the k-NN Method

Abstract

The need to measure urban link travel time (ULTT) is becoming increasingly important for network management and traveler information provision. This paper proposes the use of the k nearest neighbors ( k-NN) technique to estimate ULTT with the use of single loop inductive loop detector (ILD) data. Real-world data from London is used. This paper explores the sensitivity of travel time estimates to various k-NN design parameters. It finds that the k-NN method is not particularly sensitive to the distance metric, although care must be taken in selecting the right combination of local estimation method (LEM) and value of k. A robust LEM should be used. The optimized k-NN model is found to provide more accurate estimates than other ULTT methods. To obtain a more accurate estimate of ULTT, a potential application of this approach could be to aggregate GPS probe vehicle ULTT records from different times but the same underlying travel time distribution.