A Method for Locational Risk Estimation of Vehicle–Children Accidents Considering Children’s Travel Purposes

Kojiro Matsuo (), Kosuke Miyazaki and Nao Sugiki
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Kojiro Matsuo: Department of Architecture and Civil Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan
Kosuke Miyazaki: Department of Civil Engineering, National Institute of Technology, Kagawa College, Kagawa 761-8058, Japan
Nao Sugiki: Department of Architecture and Civil Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan

IJERPH, 2022, vol. 19, issue 21, 1-16

Abstract: The reduction in locational traffic accident risks through appropriate traffic safety management is important to support, maintain, and improve children’s safe and independent mobility. This study proposes and verifies a method to evaluate the risk of elementary school students-vehicle accidents (ESSVAs) at individual intersections on residential roads in Toyohashi city, Japan, considering the difference in travel purposes (i.e., school commuting purpose; SCP or non-school commuting purpose: NSCP), based on a statistical regression model and Empirical Bayes (EB) estimation. The results showed that the ESSVA risk of children’s travel in SCP is lower than that in NSCP, and not only ESSVAs in SCP but also most ESSVAs in NSCP occurred on or near the designated school routes. Therefore, it would make sense to implement traffic safety management and measures focusing on school routes. It was also found that the locational ESSVA risk structure is different depending on whether the purpose of the children’s travels is SCP or NSCP in the statistical model. Finally, it was suggested that evaluation of locational ESSVA risks based on the EB estimation is useful for efficiently extracting locations where traffic safety measures should be implemented compared to that only based on the number of accidents in the past.

Keywords: elementary school students; locational accident risk; travel purpose; Empirical Bayes estimation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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