Papers

Peer-reviewed
2018

TRAFFIC ACCIDENT RISK ESTIMATION MODEL FOR RESIDENTIAL STREETS USING ETC2.0 PROBE DATA

Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management)
  • TSUBOTA Takahiro
  • ,
  • YOSHII Toshio
  • ,
  • KURAUCHI Shinya
  • ,
  • YAMAMOTO Atsushi

Volume
74
Number
5
First page
I_1029
Last page
I_1035
Language
Japanese
Publishing type
Research paper (scientific journal)
DOI
10.2208/jscejipm.74.I_1029
Publisher
Japan Society of Civil Engineers

This study aims to develop traffic accident risk models for residential streets by utilising probe data. Residential streets are minor access roads in residential area for the residents to reach major arterial roads. The residential streets are not designed for heavy traffic, and thus are characterised by narrow road width and the absence of traffic lights. Nevertheless, they are often bypassed by through-traffic, due to which traffic accident risk is considered to be very high. However, the residential streets are rarely equipped with traffic sensors; traffic accident risk has not been evaluated in such minor roads, which hinders designing effective traffic safety measures. This study utilises probe vehicle information retrieved from ETC2.0 onboard equipments in order to estimate the traffic volume in the residential streets. Then, the traffic accident risks are estimated for different accident types, followed by the development of traffic accident risk estimation model based on linear regression analysis. A case study conducted in Matsuyama in Ehime prefecture revieled that the accident risk in residential areas near major arterial roads tend to be higher. The residential streets in office areas and in the areas with higher population of working ages are also identified as having higher accident risks. The findings would be useful inputs in planning the counter strategies and in prioritising the areas to be improved.

Link information
DOI
https://doi.org/10.2208/jscejipm.74.I_1029
J-GLOBAL
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201702222704158439
CiNii Articles
http://ci.nii.ac.jp/naid/130007556200
URL
http://jglobal.jst.go.jp/public/201702222704158439

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