• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.5
• /
• pp.2743-2748
• /
• 2014

The research was conducted to understand the correlation between sensory processing ability and safe driving behavior of over 65. Questionnaires regarding sensory processing ability and safe driving behavior were given to 31 people who are in their 65 or over and Pearson Correlation Analysis was carried out on the survey. The result of the research indicates that there is interrelationship between total score of sensory processing ability and safe driving behavior, and sub factors. According to the findings, over 65 showed certain difficulties in sensory processing ability and safe driving behavior due to aging. Therefore, it would be necessary to evaluate their driving behavior and arbitrate appropriate operation therapy.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.4
• /
• pp.65-72
• /
• 2008

The Manchester Driver Behavior Questionnaire (DBQ) is the most commonly used frameworks for investigating the relationship between self-reported driving behavior and accident involvement. After Reason et al. introduced DBQ, there were many studies replicating the research of Reason et al. in many countries. There was, however, no study replication of the Reason's research in Korea. The aim of this study is to replicate the distinction among errors, lapses and violations, and to evaluate the relationship of these behaviors with road traffic accidents on Korean drivers. 223 Korean drivers completed the Korean version of original DBQ with questions regarding background information, such as age, gender, annual mileage and accident involvement. Participants answered self-assessment questions, also. Factor analysis revealed three factors like Reason et al. The three factors were dangerous errors, violations and relatively harmless errors.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.3
• /
• pp.28-38
• /
• 2017

The study is to analyze the aggressive driving behavior in the protected/permissive left turn(PPLT) intersections in Gunsan City. As a result of the logistic regression model, increasing of driver's age and driving experience, non-peak time, no company, sedan and male have a tendency to behave aggressive driving to the opposite vehicles. When the vehicles try to turn the unprotected left in the PPLT intersection, the opposite vehicle drivers recognize them at the aggressive driving behavior if the distance to opposite vehicles is not enough. The relationship between driver characteristics and the distance to the opposite vehicles is analyzed under aggressive driving behavior. increasing of age and company, peak time tend to influence the short distance opposite vehicles while male and higher driving experience the middle and long distance. Sedan has the aggressive possibility to shorter distance opposite vehicles rather than others.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.1
• /
• pp.67-71
• /
• 2009

Using driving simulator, we analyzed the driving behavior of an older driver on intersection and measured the pychological load to HRV. As a results, older drivers started to enter the more complex intersection on a great distance and on low velocity for safety driving. On the other hand, the value of HRV would be lower on more complex intersections. It suggested that an older driver allowed for his own losses of physiological and cognitive function and recognized low level of driving confidence relatively.

• Safety and Health at Work
• /
• v.13 no.2
• /
• pp.187-191
• /
• 2022

Background: Traffic injuries have become a significant public health problem in low- and middle-income countries. Several studies have examined the role of personality and attitude toward traffic safety in predicting driving behaviors in diverse types of drivers. Few studies have investigated risky behavior among public passenger van drivers. This study aims to identify the predictors of self-reported risky driving behavior among public van drivers. Method: A total of 410 public van drivers were interviewed at terminal stations in Bangkok. Hierarchical regression models were applied to determine the effects of demographics, personality traits, and attitude on self-reported risky driving behaviors. Results: The results indicated that drivers with a high education level, more working days, and high scores for normlessness and anger were more likely to report risky driving behaviors (p < 0.05). Conclusion: The personality traits and attitude toward speeding account for aberrant self-reported risky driving behavior in passenger van drivers. This could be another empirical basis for evidence-based road safety interventions in the context of public transport.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.5
• /
• pp.735-739
• /
• 2010

Driving workload is increasing according to developing new in-vehicle devices and introducing driving information systems. In this research using a driving simulator, EFRP (Eye Fixation Related Potential) was measured for evaluating driving attention and distraction while tasking cognitive workload, n-back tasks. The result of EFRP was compared with driver behaviors. Results suggest that EFRP is able to use for a method of evaluating driving workload, however, the analysis of driver behavior is difficult to find driving attention and distraction in the case of free flow of traffic situation.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.2
• /
• pp.119-128
• /
• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.8
• /
• pp.33-39
• /
• 2017

In this paper, we propose a method which implements warning to drivers through real-time analysis of risky and unexpected driver and vehicle behavior using only a smartphone without using data from digital tachograph and vehicle internal sensors. We performed the evaluation of our system that demonstrates the effectiveness and usefulness of our method for risky and unexpected driver and vehicle behavior using three information such as vehicle speed, azimuth and GPS data which are acquired from a smartphone sensors. We confirmed the results and developed the smartphone application for validate and conducted simulation using actual driving data. This novel functionality of the smartphone application enhances drivers' situational awareness, increasing safety and effectiveness of driving.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.4
• /
• pp.611-617
• /
• 2010

To find out why elderly drivers have more frequent traffic accidents on intersection than any other one, this study was conducted to examine the characteristics of elderly drivers' driving behavior on intersection using a multifaceted driving behavior indicator. To do that, the driving behavior of both young adult drivers and elderly drivers were compared and analyzed, using a graphic driving simulator. As a result, compared with young adult drivers, elderly drivers showed a poor driving performance, and a high ratio of visual scanning time on the specific direction regardless of driving situation. Also, compared with young adult drivers, elderly drivers had a high overall level of arousal, and the phasic arousal activity on the specific stimulus was low. These results imply that through the intervention which induces the change in multifaceted indicators mentioned earlier, they could be helped to drive more safely on intersection.

• Journal of Convergence for Information Technology
• /
• v.11 no.4
• /
• pp.161-167
• /
• 2021

This study was conducted to identify the relationship between the dual task performance and driving behavior of the elderly driver in order to identify whether the dual task can be utilized as a test to screen the driving ability of the elderly driver. We surveyed general information and driving-related information for 32 normal elderly drivers, and evaluated Y-DuCog(Yonsei-Dual task Cognitive screening) and the K-DBQ (Korean-Driving Behavior Questionnaire). As a result of the study, the performance of the dual task using the pegboard task and the animal name speaking showed a significant correlation with the score of the violation domain of K-DBQ. With this study, it was possible to confirm the possibility as a test for discrimination of driving ability.