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Factors associated with pedestrian-vehicle collision hotspots involving seniors and children: a deep learning analysis of street-level images.

Factors associated with pedestrian-vehicle collision hotspots involving seniors and children: a deep learning analysis of street-level images.

Authors :
Jun, Hee-Jung
Jung, Suyoung
Kang, Seungyeoup
Kim, Taewan
Cho, Cheol-Ho
Jhoo, Won Young
Heo, Jae-Pil
Source :
International Journal of Urban Sciences; Jun2024, Vol. 28 Issue 2, p359-377, 19p
Publication Year :
2024

Abstract

This study aimed to examine the factors associated with pedestrian–vehicle collision hotspots involving seniors and children. For the empirical analysis, we first quantified street-level images of collision hotspots involving seniors and children and non-collision hotspots in the Seoul Metropolitan Area, Korea, using deep learning analysis. Thereafter, we examined the risk factors associated with collision hotspots through logistic analyses. This study has two major findings. First, the effects of risk factors (e.g. share of sky and green space) differ between collision hotspots involving seniors and children. Second, some pedestrian safety treatments (i.e. traffic lights and sidewalks) are positively associated with collision risks. The findings suggest that varied approaches to enhancing pedestrian safety among different age groups should be considered for more effective pedestrian safety interventions. In addition, the quality of pedestrian safety measures should be examined to improve pedestrian safety for seniors and children. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
12265934
Volume :
28
Issue :
2
Database :
Complementary Index
Journal :
International Journal of Urban Sciences
Publication Type :
Academic Journal
Accession number :
176986083
Full Text :
https://doi.org/10.1080/12265934.2023.2282190