• Journal of Digital Convergence
• /
• v.19 no.4
• /
• pp.25-31
• /
• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.12
• /
• pp.468-474
• /
• 2019

Korea had the highest accident rate among OECD countries in 2018, with 8.4 per 100,000 population, ranking 4th among 35 countries. In addition, the accident rate of traffic with children and the elderly was also high. This study reviewed the relevant literature and analyzed the traffic-accident analysis system. Customized traffic safety facilities were developed. In addition, by measuring the visibility of the traffic safety facilities by installing a test bed, this study measured the forward driving frequency and vehicle driving speed while driving. As a result of applying the "pedestrian pedestrian model" collision test model, the possibility of serious injury after installing the facility was reduced greatly to 4.6%. In this study, the visibility of traffic safety facilities and the effect of reducing the traffic speed were verified through test beds. Recognizing traffic safety facilities will reduce traffic accidents.

• Journal of Chest Surgery
• /
• v.46 no.2
• /
• pp.130-134
• /
• 2013

Background: Rib fractures are the most common type of thoracic trauma and cause other complications. We explored the risk factors for pneumonia in patients with multiple rib fractures. Materials and Methods: Four hundred and eighteen patients who visited our hospital with multiple rib fractures between January 2002 and December 2008 were retrospectively reviewed. Chest X-rays and chest computed tomography were used to identify injury severity. Patients with only a single rib fracture or who were transferred to another hospital within 2 days were excluded. Results: There were 327 male patients (78%), and the median age was 53 years. The etiologies of the patients' trauma included traffic accidents in 164 cases (39%), falls in 78 cases (19%), slipping and falling in 90 (22%), pedestrian accidents in 30 (7%), industrial accidents in 41 (10%), and assault in 15 (4%). The median number of rib fractures was 4.8. Pulmonary complications including flail chest (2.3%), lung contusion (22%), hemothorax (62%), pneumothorax (31%), and hemopneumothorax (20%) occurred. Chest tubes were inserted into the thoracic cavity in 216 cases (52%), and the median duration of chest tube insertion was 10.26 days. The Injury Severity Score (ISS) and rib score had a median of 15.27 and 6.9, respectively. Pneumonia occurred in 18 cases (4.3%). Of the total cases, 33% of the cases were managed in the intensive care unit (ICU), and the median duration of stay in the ICU was 7.74 days. Antibiotics were administered in 399 patients (95%) for a median of 10.53 days. Antibiotics were used for more than 6 days in 284 patients (68%). The factors affecting pneumonia in patients with multiple rib fractures in multivariate analysis included age (p=0.004), ISS (p<0.001), and rib score (p=0.038). The use of antibiotics was not associated with the occurrence of pneumonia (p=0.28). In-hospital mortality was 5.3% (n=22). Conclusion: The factors affecting risk of pneumonia in patients with multiple rib fractures included age (p=0.004), ISS (p<0.001), and rib score (p=0.038). Elderly patients with multiple traumas have a high risk of pneumonia and should be treated accordingly.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.61-68
• /
• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.