Safety Analysis of Motorcycle Crashes in Seoul Metropolitan Area, South Korea: An Application of Nonlinear Optimal Scaling Methods

Younshik Chung and Tai-Jin Song
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Younshik Chung: Department of Urban Planning and Engineering, Yeungnam University, Gyeongsan 38541, Korea
Tai-Jin Song: Department of National Transport Big Data, The Korea Transport Institute, Sejong 30147, Korea

IJERPH, 2018, vol. 15, issue 12, 1-20

Abstract: This study identifies the critical factors that affect motorcycle crash severity based on Korean motorcycle crash data in 2009. Motorcyclists, the environment, roadways, other vehicles involved in the crashes, and traffic flow characteristics were used as variables for identifying critical factors. Multivariable statistical methods were used to analyze the data, including categorical principal components analysis (CatPCA) and nonlinear canonical correlation analysis (NLCCA). The results indicate that the following factors are the most critical in increasing motorcycle crash severity: age (motorcyclists in their teens and over fifty years old), motorcycle speed over 30 km/h, speed over 50 km/h for other vehicles involved in the crash, crashes with heavy vehicles such as buses and trucks, crashes on roadways less than six meters wide, crashes at curved sections, crashes at basic roadway segments without any speed control facilities, and head-on crashes. These findings are expected to serve as a valuable reference for formulating remedial policy measures to decrease the severity of motorcycle crashes on roadways in the Seoul metropolitan area of South Korea.

Keywords: motorcycle crash; motorcyclist injury severity; optimal scaling; categorical principal components analysis; nonlinear canonical correlation analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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