File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

조기혁

Cho, Gi-Hyoug
Sustainable Urban Planning and Design Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

An examination of the intersection environment associated with perceived crash risk among school-aged children: using street-level imagery and computer vision

Author(s)
Kwon, Jae-HongCho, Gi-Hyoug
Issued Date
2020-10
DOI
10.1016/j.aap.2020.105716
URI
https://scholarworks.unist.ac.kr/handle/201301/50083
Fulltext
https://www.sciencedirect.com/science/article/pii/S0001457519315398?via%3Dihub#!
Citation
ACCIDENT ANALYSIS AND PREVENTION, v.146, pp.105716
Abstract
While computer vision techniques and big data of street-level imagery are getting increasing attention, a "black-box" model of deep learning hinders the active application of these techniques to the field of traffic safety research. To address this issue, we presented a semantic scene labeling approach that leverages wide-coverage street-level imagery for the purpose of exploring the association between built environment characteristics and perceived crash risk at 533 intersections. The environmental attributes were measured at eye-level using scene segmentation and object detection algorithms, and they were classified as one of four intersection typologies using the k-means clustering method. Data on perceived crash risk were collected from a questionnaire conducted on 799 children 10 to 12 years old. Our results showed that environmental features derived from deep learning algorithms were significantly associated with perceived crash risk among school-aged children. The results have revealed that some of the intersection characteristics including the proportional area of sky and roadway were significantly associated with the perceived crash risk among school-aged children. In particular, road width had dominant influence on risk perception. The findings provide information useful to providing appropriate and proactive interventions that may reduce the risk of crashes at intersections.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
ISSN
0001-4575
Keyword
BUILT ENVIRONMENTTRAFFIC SAFETYPERCEPTIONVIEWVEHICLEWALKINGHAZARDNEIGHBORHOODSRELIABILITYVISIBILITY

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.