• 한국심리학회지 : 문화 및 사회문제
• /
• 제12권5호_spc
• /
• pp.149-167
• /
• 2006

고령화가 다른 국가에 비해 상대적으로 빠르게 진행되고 있는 상황에 대비한 고령운전자의 연구가 부족한 실정이다. 본 연구는 고령운전자의 교통사고 원인을 신체적 능력저하보다도 심리적 요인의 변화에 입각하여 고찰해 보려고 한다. - 고령운전자의 교통사고 고령운전자의 교통사고에서 가장 두드러지게 나타나는 행동적 특징은 좌회전시 발생하는 교통사고가 많다는 것이다. 그리고 사고장소에 따른 분석결과에 의하면, 교차로에서 발생하는 사고가 많다는 것이 확인되었다. - 고령운전자의 조심성과 보상행동 고령운전자의 조심성이 운전행동에 미치는 알아보기 위하여 운전자의 운전확신수준을 비교해 보았다 운전확신수준은 4개 요인으로 구분되었고, 고령운전자와 젊은 운전자의 운전확신수준 차이를 검증한 결과를 보면, 고령운전자의 운전확신수준이 젊은 운전자에 비해 현저하게 떨어지는 것을 알 수 있었다 그리고 좌회전을 선택시 소요되는 시간을 분석하여 고령운전자의 조심성을 이해하려고 하였다 고령운전자는 젊은 운전자에 비해 선택소요시간이 현저하게 길어진다는 사실을 발견하였다. - 고령운전자의 운전일탈행동 연령에 따른 운전일탈행동의 변화를 보면, 연령이 증가함에 따라 운전일탈행동의 위반, 오류, 착오의 평균 점수는 감소하는데, 각 요인이 감소하는 정도는 차이가 있었다. 위반점수는 연령의 증가에 따라 급격하게 감소하는 모습을 보이는데 비해 오류와 착오점수는 연령의 증가에 따라 완만하게 감소하는 경향을 보였다.

• International Journal of Computer Science & Network Security
• /
• 제24권3호
• /
• 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.

• 한국컴퓨터정보학회논문지
• /
• 제26권11호
• /
• pp.173-182
• /
• 2021

본 논문에서는 운전자의 주의산만을 유발하는 운전자, 탑승자의 동작을 분석하고 핸드폰과 관련된 운전자의 행동 10가지를 인식하였다. 먼저 주의산만을 유발하는 동작을 환경 및 요인으로 분류하고 관련 최근 논문을 분석하였다. 분석된 논문을 기반으로 주의산만을 유발하는 주요 원인인 핸드폰과 관련된 10가지 운전자의 행동을 인식하였다. 약 10만 개의 이미지 데이터를 기반으로 실험을 진행하였다. SURF를 통해 특징을 추출하고 3가지 모델(CNN, ResNet-101, 개선된 ResNet-101)로 실험하였다. 개선된 ResNet-101 모델은 CNN보다 학습 오류와 검증 오류가 8.2배, 44.6배가량 줄어들었으며 평균적인 정밀도와 f1-score는 0.98로 높은 수준을 유지하였다. 또한 CAM(class activation maps)을 활용하여 딥러닝 모델이 운전자의 주의 분산 행동을 판단할 때, 핸드폰 객체와 위치를 결정적 원인으로 활용했는지 검토하였다.

• 한국산업융합학회 논문집
• /
• 제5권3호
• /
• 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.

• 한국컴퓨터정보학회논문지
• /
• 제20권12호
• /
• 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.

• 대한인간공학회지
• /
• 제31권2호
• /
• 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
• /
• 제11권2호
• /
• 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.

• 한국ITS학회 논문지
• /
• 제14권4호
• /
• pp.86-94
• /
• 2015

최근 커넥티드 카는 자동차 업계 뿐 아니라 통신업체 등 다양한 산업분야에서 큰 주목을 받고 있다. 자동차도 하나의 디바이스로 인식되고 다양한 기기와 연동되면서 상호 작용하는 시스템으로 발전하고 있고 새로운 형태의 사업기회가 생겨나고 있다. 하지만 차량용 기술 발전에 따라 사고의 위험성 또한 대두되고 있으며 운전자의 사고를 예방하기 위한 다양한 기술들이 여러 기관에서 연구되고 있다. 본 연구에서는 운전자의 사고를 예방하기 위한 운전부하에 대하여 연구하고, 선행 된 연구에 바탕을 두고 운전자의 행동을 판단하여 운전부하를 측정하는 개발하였다. 개발된 알고리즘은 도로 주행 실험을 통하여 다양한 도로상황, 운전자의 상태에 따른 운전행동과 운전부하에서 유효하게 작동함을 확인할 수 있었다.

• International Journal of Computer Science & Network Security
• /
• 제22권11호
• /
• 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.

• 한국멀티미디어학회논문지
• /
• 제25권2호
• /
• 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.