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http://dx.doi.org/10.12815/kits.2021.20.5.113

Optimize TOD Time-Division with Dynamic Time Warping Distance-based Non-Hierarchical Cluster Analysis  

Hwang, Jae-Yeon (Univ. of Hannam)
Park, Minju (Dept. of Big Data Application, Univ. of Hannam)
Kim, Yongho (Dept. of Metropolitan Transport, Korea Transport Institute)
Kang, Woojin (Dept. of Metropolitan Transport, Korea Transport Institute)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.20, no.5, 2021 , pp. 113-129 More about this Journal
Abstract
Recently, traffic congestion in the city is continuously increasing due to the expansion of the living area centered in the metropolitan area and the concentration of population in large cities. New road construction has become impossible due to the increase in land prices in downtown areas and limited sites, and the importance of efficient data-based road operation is increasingly emerging. For efficient road operation, it is essential to classify appropriate scenarios according to changes in traffic conditions and to operate optimal signals for each scenario. In this study, the Dynamic Time Warping model for cluster analysis of time series data was applied to traffic volume and speed data collected at continuous intersections for optimal scenario classification. We propose a methodology for composing an optimal signal operation scenario by analyzing the characteristics of the scenarios for each data used for classification.
Keywords
Traffic signal control; Signal scenario; TOD; Cluster analysis; Dynamic Time Warping;
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