00968434

Component

https://doi.org/10.3141/1856-02

http://scholar.google.com...shak&publication_year=2003

Information is a key component of today's surface transportation systems. Yet the quality of information is often determined by the quality of raw data from which it is extracted. A plethora of data is currently being compiled in real time from hundreds of miles of freeway sections nationwide. A large proportion of the data is collected via inductive loop detectors and is vital to the successful implementation of transportation data warehouses and decision support systems. Little effort has been made to establish procedures that quantify the amount of uncertainties in the traffic observations and enhance data screening algorithms. This study presents an approach derived from a fuzzy-clustering concept to measure the level of uncertainties associated with dual loop detector observations. The developed algorithm does not rely on a specific mathematical model and avoids estimating the effective vehicle length because of the limitations explained here. Based on a divide-and-conquer approach, the algorithm clusters the input space of the three traffic parameters (speed, occupancy, and volume) into regions of highly concentrated observations. The level of uncertainty in each observation can then be measured with one parameter that is derived from the membership grade and a decaying function of the normalized Euclidean distance. The parameter can thus be used for data screening as well as detector maintenance and recalibration purposes. A data screening algorithm was developed to identify erroneous observations in four sequential stages. The results obtained from screening 50,000 observations indicate that most of the noise cluttering the input space was significantly reduced by setting the uncertainty measure to 0.9.

This paper appears in Transportation Research Record No. 1856, Freeways, High-Occupancy Vehicle Systems, and Traffic Signal Systems 2003.

English

p. 6-15

2003

Transportation Research Record

0309085926

Figures (7) ; References (18)

Algorithms; Data collection; Freeways; Interference; Lane occupancy; Loop detectors; Traffic speed; Traffic volume; Uncertainty

Data screening; Fuzzy clustering; Recalibration

Highways; Operations and Traffic Management; I71: Traffic Theory

TRIS, TRB, ATRI

Jan 2 2004 12:00AM

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