• Journal of Korean Society of Transportation
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• v.15 no.1
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• pp.17-26
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• 1997

최근에 이르러 자동차의 대수는 급격히 증가해 왔다. 이런 경향성의 결과로 나타난 교통사고의 인적 및 물질적인 손실이 최악의 상태에 이르른 것이 사실상 오늘날 우리들의 불행한 현실이다. 대다수의 교통사고가 운전자의 교통법규 위반에 기인되고 있다는 전제하 에 본 논문은 심리학적인 관점에서 그와같은 위반적인 운전자 행동의 이론적 배경을 비판적으로 분석하고자 시도한다. 아울러 이 논문에서는 운전자의 법규 위반적 행동에 대해 취할 수 있는 기본적이 대책을 마련 하는데 있어 특별히 기여할 수 있을 "인간-환경-경험" 모델을 구축하는 기초를 마련하고자 노력하고 있다.자 노력하고 있다.

• Review of KIISC
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• v.33 no.4
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• pp.41-46
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• 2023

운전자의 편의성 및 안정성 향상을 위해, 차량에 탑재되는 다양한 센서 및 전자제어장치들은 주행 중 많은 양의 데이터들을 생성한다. 이렇게 생성된 많은 양의 데이터들의 분석은 개인화 서비스, 자동차 보험, 사고 예측와 같은 곳에 활용되고 있다. 최근 주행 중의 다양한 데이터 종류와 머신러닝 및 딥러닝 기반의 방법론을 통해 차량의 운전자를 식별하는 연구들이 진행되고 있다. 본 고에서는 차량에서의 데이터 분석에 기반한 운전자 식별 연구 동향을 설명하도록 하겠다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.115-122
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• 2016

This paper proposes a system to detect driver's cognitive state by internal and external information of vehicle. The proposed system can measure driver's eye gaze. This is done by concept of information delivery and mutual information measure. For this study, we set up two web-cameras at vehicles to obtain visual information of the driver and front of the vehicle. We propose Gestalt principle based selective attention model to define information quantity of road scene. The saliency map based on gestalt principle is prominently represented by stimulus such as traffic signals. The proposed system assumes driver's cognitive resource allocation on the front scene by gaze analysis and head pose direction information. Then we use several feature algorithms for detecting driver's characteristics in real time. Modified census transform (MCT) based Adaboost is used to detect driver's face and its component whereas POSIT algorithms are used for eye detection and 3D head pose estimation. Experimental results show that the proposed system works well in real environment and confirm its usability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.11-19
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• 2008

Currently, existing car following models among several basic systems of advanced vehicle systems are almost developed related to the physical relation between two vehicles except for the driver's behavior or environmental factors. But the consideration of driver's character and environmental factors on driving are very essential factors for actual application. Hence, we suggested calibrating the degree of driver's discomfort on driving that is the former study to develop a new car following model of advanced vehicle to use in actuality. The degree of driver's discomfortness (Measure-of-Alarmness; MOA)is measured related to the relationship between the following vehicle and the preceding vehicle, the environmental factors and driver's characters in ubiquitous traffic. We made up questions to drivers to obtain the general and the objective measurement of driver's MOA. And the fuzzy logic model for measurement of MOA was constructed based on the results of survey. We verified the suitability of fuzzy logic model through the computation of MOA with several scenarios. And we measured the quantitative degree of driver's discomfortness on car following related to several factors which affect drivers. In accordance with this study, development of car following model applying driver's MOA will promote the actual application of advanced vehicle more effectively than the existing models. Finally, we thought the measurement of driver's MOA will be applied significantly to evaluate safety and comfort of drivers on driving.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.111-122
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• 2004

The driver's decision making (e.g. route choice) is a typical decision making with an uncertainty. In this paper, we investigate the effect of route guidance information on driver's route choice and learning behavior and analyse the potential of information system in a road network in which traffic flows follow random walk. A Simulation performed focuses on the relationship among the network wide performance, message receiving rates and driver's learning mechanism. We know that at high levels of message receiving rates, the network-wide performance may get worse. However, at low levels of receiving rates, we found that the travel time when guidance information is provided decrease compared to the cases when no pubic information is provided. Also, we found that the learning parameter of the learning mechanism model always changes under nonstationary traffic condition. In addition, learning process of drivers does not converge on any specific value. More investigation is needed to enlarge the scope of the study and to explore more deeply driver's behavior.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.111-118
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• 2009

Factors causing traffic accidents are various and traffic law violations can be among them. The efforts to increase traffic law obedience rates of drivers are common in many other countries to reduce traffic accidents, and one of generally applied methods is to increase the amounts of violation fines. Expensive levels of traffic law violation fines could have drivers choose "obey the law" in their decision-making stages since they are economically better-off by following the law. In this sense, this study has developed an economic model to verify whether the current levels of the traffic violation fines of Korea are effective for drivers to choose "obey-the-law" decisions. Speed violations and traffic signal violations have been selected for the case study to verify the relationships between "expected probabilities of being-caught" and "levels of violations fines".

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.106-118
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• 2014

The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.

• Convergence Security Journal
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• v.12 no.6
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• pp.31-37
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• 2012

Today, the core technology of an automobile is becoming to IT-based convergence system technology. To cope with many kinds of situations and provide the convenience for drivers, various IT technologies are being integrated into automobile system. In this paper, we propose an convergence system, which is called Augmented Driving System (ADS), to provide high safety and convenience of drivers based on image information processing. From imaging sensor, the image data is acquisited and processed to give distance from the front car, lane, and traffic sign panel by the proposed methods. Also, a converged interface technology with camera for gesture recognition and microphone for speech recognition is provided. Based on this kind of system technology, car accident will be decreased although drivers could not recognize the dangerous situations, since the system can recognize situation or user context to give attention to the front view. Through the experiments, the proposed methods achieved over 90% of recognition in terms of traffic sign detection, lane detection, and distance measure from the front car.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.139-146
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• 2004

Road design should be conformed to the expectancy of drivers. The alignment such as long tangent followed by the sharp horizontal curve should be avoided for the road design consistency. Currently, operating speed profile model is generally used to check the consistency of the successive road alignments. In this model, the hypothesis about the drivers' behaviour on the long tangent followed by the sharp horizontal curve is also included. This study compares the hypothesized drivers' behaviour in the existing operating speed profile model with the actual drivers' behaviour observed at the two lane rural roads. In addition to this, comparison between the acceleration for the vehicles approaching and departing horizontal curves suggested by the foreign research and the value observed at this study was made, From this study, it was concluded that the hypothesis in the existing model was well representing the actual drivers' behaviour. The deceleration for vehicles approaching the horizontal curves was ranged $0.39{\sim}1.06m/s^2$ with the average of $0.66m/s^2$. The average acceleration for the vehicles departing horizontal curves was $0.22m/s^2$.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.61-73
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• 2010

This research is to analyze reasons for violation of the Self Carfree day policy. It also analyzes satisfaction of the policy participation incentives. The results are that the violation rate is increasing if the drivers live in a zone which is highly energy consuming, which has low potential demand per bus stop and low trip generation per number of houses, which therefore requires more bus routes and bus services, and in which the drivers pay more car operating fees and show less tendancy towards participation even with the 5-10% oil price increase. The results are significant at the 0.05 level.