@article{ART003109524},
author={Tae-Wook Kim and Ji-Woong Yang and Hyeon-Jin Jung and Han-Jin Lee and Ellen J. Hong},
title={Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={8},
pages={53-58},
doi={10.9708/jksci.2024.29.08.053}
TY - JOUR
AU - Tae-Wook Kim
AU - Ji-Woong Yang
AU - Hyeon-Jin Jung
AU - Han-Jin Lee
AU - Ellen J. Hong
TI - Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 8
PB - The Korean Society Of Computer And Information
SP - 53
EP - 58
SN - 1598-849X
AB - Traffic accidents are not only a threat to human lives but also pose significant societal costs. Recently, research has been conducted to address the issue of traffic accidents by predicting the risk using deep learning technology and spatiotemporal information of roads. However, while traffic accidents are influenced not only by the spatiotemporal information of roads but also by human factors, research on the latter has been relatively less active. This paper analyzes driver groups and characteristics by applying clustering techniques to a traffic accident dataset and proposes and applies a method to calculate the Risk Level for each driver group and characteristic. In this process, the preprocessing technique suggested in this paper demonstrates a higher Silhouette Score of 0.255 compared to the commonly used One-Hot Embedding & Min-Max Scaling techniques, indicating its suitability as a preprocessing method.
KW - Traffic accident;Clustering;Risk level;Embedding;Preprocessing
DO - 10.9708/jksci.2024.29.08.053
ER -
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee and Ellen J. Hong. (2024). Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention. Journal of The Korea Society of Computer and Information, 29(8), 53-58.
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee and Ellen J. Hong. 2024, "Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention", Journal of The Korea Society of Computer and Information, vol.29, no.8 pp.53-58. Available from: doi:10.9708/jksci.2024.29.08.053
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee, Ellen J. Hong "Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention" Journal of The Korea Society of Computer and Information 29.8 pp.53-58 (2024) : 53.
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee, Ellen J. Hong. Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention. 2024; 29(8), 53-58. Available from: doi:10.9708/jksci.2024.29.08.053
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee and Ellen J. Hong. "Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention" Journal of The Korea Society of Computer and Information 29, no.8 (2024) : 53-58.doi: 10.9708/jksci.2024.29.08.053
Tae-Wook Kim; Ji-Woong Yang; Hyeon-Jin Jung; Han-Jin Lee; Ellen J. Hong. Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention. Journal of The Korea Society of Computer and Information, 29(8), 53-58. doi: 10.9708/jksci.2024.29.08.053
Tae-Wook Kim; Ji-Woong Yang; Hyeon-Jin Jung; Han-Jin Lee; Ellen J. Hong. Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention. Journal of The Korea Society of Computer and Information. 2024; 29(8) 53-58. doi: 10.9708/jksci.2024.29.08.053
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee, Ellen J. Hong. Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention. 2024; 29(8), 53-58. Available from: doi:10.9708/jksci.2024.29.08.053
Tae-Wook Kim, Ji-Woong Yang, Hyeon-Jin Jung, Han-Jin Lee and Ellen J. Hong. "Driver Group Clustering Technique and Risk Estimation Method for Traffic Accident Prevention" Journal of The Korea Society of Computer and Information 29, no.8 (2024) : 53-58.doi: 10.9708/jksci.2024.29.08.053