• Korean Journal of Culture and Social Issue
• /
• v.12 no.5_spc
• /
• pp.149-167
• /
• 2006

Korean society is rapidly changing to aging society comparing the other industrialized countries, however, the studies of elderly driver's driving behavior and accidents are not enough in Korea for elderly driver's accident prevention. This study focused on the elderly driver's psychological effects on elderly driver's driving behavior and traffic accidents; carefulness and aberrant driving behavior. - Elderly driver's traffic accidents The high percentage of elderly driver's accidents occurs in intersections and when turning left. There was a significant difference of the opponent vehicle's speed when left turn, between elderly driver and young driver; the elderly driver choose the higher speed of opponent vehicle than young driver when left turning. This result means that elderly driver has some problems with deciding the vehicle's speed and gap acceptance(Sunyeol Lee, Soonchul Lee, and Inseok Kim, 2006)(Table 1). - Carefulness and driving confidence In order to understand elderly driver's carefulness, this study compared the elderly driver's driving confidence. Driving confidence was consisted of 4 factors; environment of traffic condition, safe driving, driving ability and attention. Elderly driver's confidence was lower than young driver's. Elderly driver in high driving confidence group, showed longer driving history and they were tend to commit violations more frequently than elerly driver in low driving confidence group. Young driver, whose driving confidence level was high answered more driving history, annual mileage, the frequency of committing traffic violation and the experience of accident within lats 5 years(Soonchul Lee, Juseok Oh, Sunjin Park, Soonyeol Lee and Inseok Kim, 2006)(Table 2). This study examined the total time required until deciding to turn left in the no traffic signal intersection between elderly driver and young driver. The result showed that the time of elderly driver was significant longer than young driver(Sunyeol Lee et al, 2006)(Table 3). - Elderly driver's aberrant behavior Driver behavior Questionnaire(DBQ) was measured to understand the aberrant behavior; violation, error and lapse. The tend of aberrant behavior was observed by aging(Sunjin Park, Soonchul Lee, Jonghoi, Kim and Inseok Kim, 2006). Elderly driver's DBQ score was lower than young driver's(Table 4). Elderly and young driver showing longer driving history were in low DBQ score group. Elderly driver had high error score and young driver had high violation score. Young driver's aberrant driving behaviour was associated with annual mileage and the frequency of committing traffic violation. Elderly driver's aberrant driving behaviour was associated with annual mileage and experience of accident. Especially elderly driver whose violation, error and lapse score was high answered more committing experience of accident within last 5 years.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.142-150
• /
• 2024

A conceptual model represents an understanding of a system that is going to be developed, which in this research, a driving simulation software to study driver behavior at signalised intersections. Therefore, video observation was conducted to study driver compliance behaviour within the dilemma zone at signalised intersection, with regards to driver's distance from the stop line during yellow light interval. The video was analysed using Thematic Analysis and the data extracted from it was analysed using Chi-Square Independent Test. The Thematic Analysis revealed two major themes which were traffic situation and driver compliance behaviour. Traffic situation is defined as traffic surrounding the driver, such as no car in front and behind, car in front, and car behind. Meanwhile, the Chi-Square Test result indicates that within the dilemma zone, there was a significant relationship between driver compliance behaviour and driver's distance from the stop line during yellow light interval. The closer the drivers were to the stop line, the more likely they were going to comply. In contrast, drivers showed higher non-compliant behavior when further away from stop line. This finding could help in the development of conceptual model of driving simulation with purpose in studying driver behavior.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.11
• /
• pp.173-182
• /
• 2021

In this paper, we analyzed driver's and passenger's motions that cause driver's distraction, and recognized 10 driver's behaviors related to mobile phones. First, distraction-inducing behaviors were classified into environments and factors, and related recent papers were analyzed. Based on the analyzed papers, 10 driver's behaviors related to cell phones, which are the main causes of distraction, were recognized. The experiment was conducted based on about 100,000 image data. Features were extracted through SURF and tested with three models (CNN, ResNet-101, and improved ResNet-101). The improved ResNet-101 model reduced training and validation errors by 8.2 times and 44.6 times compared to CNN, and the average precision and f1-score were maintained at a high level of 0.98. In addition, using CAM (class activation maps), it was reviewed whether the deep learning model used the cell phone object and location as the decisive cause when judging the driver's distraction behavior.

• Journal of the Korean Society of Industry Convergence
• /
• v.5 no.3
• /
• pp.239-246
• /
• 2002

The propose of this study is to analysis driver's behavior of traveler information. This research made an attempt to explore driver's route change behavior in the en-route stage. Model were developed for each analysis with LIMDEP software which was developed by Willams H Greene. Commuters' transportation change in before trip stage are affected by their income, travel time, and incident information and constant of this model showed their reluctance of change mode. This was resulted from the inappropriateness of traffic information to general commuters which is the main target of traffic information.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.12
• /
• pp.37-44
• /
• 2015

In this paper, we propose the assistance method to enable safe driving through analysis of dangerous driving behavior using real-time alarm by vehicle speed, azimuth data and smartphone. For this method, smartphone is receiving driving data from digital tachograph using communication. Safe driving habit is a very important issue to commercial vehicle because that driver's long time driving than other vehicle type driver. Existing methods are very inefficient to improve immediately dangerous driving habits during driving because proceed driving behavior analysis after the vehicle operation. We propose the new safe driving assistance method that can prevent traffic accidents by real-time and improve the driver's wrong driving habits through real-time dangerous driving behavior analysis and notification the result to the driver. We have confirmed that the method in this paper will help to improve driving habits and can be applied through the proposed method implementation and simulation experiment.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.2
• /
• pp.371-377
• /
• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.

• Journal of information and communication convergence engineering
• /
• v.11 no.2
• /
• pp.95-102
• /
• 2013

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of each particular driver's behavior. In addition, general or background driving patterns are also captured with a Gaussian mixture model using a reasonably large amount of development data from several drivers. By combining both probability distributions, the aggregate driver-dependent model can better emphasize driving characteristics of each particular driver, while also backing off to exploit general driving behavior in cases of unseen/unmatched parameter spaces from individual training observations. The proposed driver behavior model was employed to anticipate pedal operation behavior during car-following maneuvers involving several drivers on the road. The experimental results showed advantages of the combined model over the model adaptation approach.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.4
• /
• pp.86-94
• /
• 2015

In recent days, a Connected Car has caught an attention of the motor companies and various industrial institutes such as communication company. An automobile is regarded as a device and has been developed as an interactive system because the system is connected with various device. This drives a new business item, too. As a new automatic car technology is emerging, a new type of car accident is appeared, too. So, many researches for preventing car accident comes from the driver's are carried out in many car related institutes. In this paper, we study a driver's driving workload and develop an algorithm that measures the driver's driving behavior. We can see that the developed algorithm runs well by the experiment of road test. This results affects various road condition, driver's driving behavior and load that reflects the driver's status.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.163-171
• /
• 2022

A conceptual model represents an understanding of a system that is going to be developed, which in this research, a driving simulation software to study driver behavior at signalised intersections. Therefore, video observation was conducted to examine driver compliance behaviour within the dilemma zone at signalised intersection, pertaining to driver's distance from the stop line during yellow light interval. The video was analysed using Thematic Analysis and the data extracted from it was analysed using Chi-Square Independent Test. The Thematic Analysis revealed two major themes which were traffic situation and driver compliance behaviour. Traffic situation is defined as traffic surrounding the driver, such as no car in front and behind, car in front, and car behind. Meanwhile, the Chi-Square Test result indicates that within the dilemma zone, there was a significant relationship between driver compliance behaviour and driver's distance from the stop line during yellow light interval. The closer the drivers were to the stop line, the more likely they were going to comply. In contrast, drivers showed higher noncompliant behavior when further away from stop line. This finding could help us in the development of conceptual model of driving simulation with purpose of studying driver behavior.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.421-431
• /
• 2022

The purpose of this research is to determine the point of fixation of the driver during the process of driving. Based on the results of this research, the driving instructor can make a judgement on what the trainee stare on the most. Traffic accidents have become a serious concern in modern society. Especially, the traffic accidents among unskilled and elderly drivers are at issue. A driver should put attention on the vehicles around, traffic signs, passersby, passengers, road situation and its dashboard. An eye-tracking-based application was developed to analyze the driver's gaze behavior. It is a prototype for real-time eye tracking for monitoring the point of interest of drivers in driving practice. In this study, the driver's attention was measured by capturing the movement of the eyes in real road driving conditions using these tools. As a result, dwelling duration time, entry time and the average of fixation of the eye gaze are leading parameters that could help us prove the idea of this study.