| Title |
Analyzing Traffic Accident Factors in Large-scale Apartment Complexes: Insights from Seoul Using Poisson Regression |
| Authors |
권형준(Kwon, Hyeong-Jun) ; 안용진(Ahn, Yong-Jin) |
| DOI |
https://doi.org/10.5659/JAIK.2024.40.5.119 |
| Keywords |
Apartment Complex; Traffic Accident in Apartment complex; Poisson Regression Model |
| Abstract |
This study examines the factors contributing to traffic accidents within apartment complexes. Seoul's vibrant apartment market offers a rich
source of data, capturing a variety of complex types over time. Data from a sample of 288 complexes with over 1,200 households in Seoul
were analyzed to understand traffic accident trends from 2019 to 2022. Using Poisson regression analysis, this study aims to identify key
factors influencing accident rates. Independent variables such as complex size, traffic flow, and neighborhood characteristics were collected
and analyzed. The analysis showed that a greater number of households in a complex raised the likelihood of traffic accidents and that
CCTV installations also had a significant effect on accident probability. The type of surrounding roads even played a role, with two-way
parallel roads presenting the highest risk, followed by two-way corner roads, three-way roads, and four-way roads. This study found that
more parking spaces per household tended to lower accident rates, while multi-way intersections increased risk. Additionally, the presence of
nearby educational facilities was associated with fewer accidents, and complexes with on-site or adjacent commercial areas experienced fewer
accidents. These findings highlight the importance of managing vehicle speed and promoting pedestrian traffic to improve safety awareness
among drivers. This study's insights can guide future planning and maintenance strategies for apartment complexes, aiming to create safer
environments for both residents and visitors. |