01337252

Component

Effective detection and correction of outliers in raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning systems (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposes a locally weighted regression (LWR) based filtering method for individual vehicle speed data. Both a technique to generate synthetic outliers and two approaches to injecting synthetic outliers are also presented to systematically evaluate the proposed method. A method to determine parameters associated with the LWR that affect the smoothing performance is devised and applied to obtain more reliable data correction. A set of illustrative evaluation examples explains that the proposed method is useful in filtering individual vehicle speed data. For the purpose of the performance comparison, an exponential smoothing method was adopted and evaluated. It was identified that the proposed LWR-based method outperformed the exponential smoothing method in performance evaluations.

01329018

11-0157

English

16p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures (10) ; References (10) ; Tables (1)

Error analysis; Global Positioning System; Mathematical models; Probe vehicles; Regression analysis; Speed; Traffic data

Vehicle speed

Data and Information Technology; Highways; I71: Traffic Theory

Transportation Research Board Annual Meeting 2011 Paper #11-0157

TRIS, TRB

Feb 17 2011 5:20PM