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http://dx.doi.org/10.12815/kits.2014.13.2.001

Study on the Classification Methodology for DSRC Travel Speed Patterns Using Decision Trees  

Lee, Minha (아주대학교 ERC 센터)
Lee, Sang-Soo (아주대학교 교통공학과)
Namkoong, Seong (한국도로공사 도로교통연구원)
Choi, Keechoo (아주대학교 교통공학과)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.13, no.2, 2014 , pp. 1-11 More about this Journal
Abstract
In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.
Keywords
DSRC; Travel patterns; Decision Tree model; historical data; Free flow speed;
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Times Cited By KSCI : 8  (Citation Analysis)
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