Using Electronic Toll Collection Data to Understand Traffic Demand

Jin-Young Kim · Fumitaka Kurauchi · Nobuhiro Uno · Takeshi Hagihara · Takehiko Daito

35 citations0/0 files storedJournal of Intelligent Transportation Systems

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Transportation Planning and Optimization Traffic control and management Traffic Prediction and Management Techniques

Abstract

In this study, we explored the potential of using electronic toll collection (ETC)-derived data that are a part of intelligent transport systems (ITS). Dynamic origin–destination (OD) traffic volumes were estimated using ETC data on the Hanshin Expressway. A dynamic OD estimation model that was suggested in a previous study was used, and abundant ETC data were input to improve the estimation accuracy. The results of OD estimation were analyzed to understand traffic demand and its variation. External factors were clarified that have an influence on variances in the OD flows, and statistical analysis methods for the variations were proposed depending on the factors. Moreover, the improvements in traffic simulation accuracy and performance as a result of using ETC data as input variables in the simulation models were discussed. According to the results of this study, ETC data have potential to assist in understaningd traffic demand and its variation, and the results can be applied to network management.

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References

1993Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts 2007Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations 2009Optimal traffic plate scanning location for OD trip matrix and route estimation in road networks 1984ESTIMATING TIME-DEPENDENT TRIP MATRICES FROM TRAFFIC COUNTS 2011Estimation of origin–destination matrices from link counts and sporadic routing data 1988Discrete time dynamic estimation model for passenger origin/destination matrices on transit networks

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