Open AccessModeling Urban Link Travel Time with Inductive Loop Detector Data by Using the k-NN Method
Author(s) -
Steve Robinson,
John Polak
Publication year - 2005
Publication title -
transportation research record
Language(s) - English
Resource type - Journals
eISSN - 2169-4052
pISSN - 0361-1981
DOI - 10.1177/0361198105193500106
Subject(s) - induction loop , metric (unit) , detector , global positioning system , computer science , measure (data warehouse) , travel time , aggregate (composite) , loop (graph theory) , sensitivity (control systems) , data mining , real time computing , simulation , engineering , mathematics , transport engineering , electronic engineering , telecommunications , operations management , materials science , combinatorics , composite material
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.