• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.29-38
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• 2023

Although the biosignal is the best way to represent the human condition, it is difficult to acquire the biosignal of a driver driving for detecting driver's condition. As one of the methods to overcome this limitation, this paper proposes a driving stress monitoring system based on information provided by OBD-II(on-board diagnostics version II). The driving information and EDA(Electrodermal activity) data are obtained through the OBD-II scanner and E4 wristband, respectively. EDA data is used as ground truth to distinguish whether driver is stressed or not. MLP(multi-layer perceptron) neural network is used as a model to detect driving stress and is trained using driving data for about a month. To evaluate the proposed system, we used about 1 hour of driving data and the accuracy is 92%.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.61-68
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• 2010

The objective of this study was to test the estimation possibility of driver's stress degrees with the HRV analysis. For this, first, HRV analysis was applied to the 5 driver's ECG signals which were acquired in 7 different stress situations. From this, the facts that HRV trend was different from that in long-distance driving and 6 parameters - meanRR, sdRR, HF, LF/HF, LFnorm, HFnorm were useful for the stress estimation in stress varying driving situation. Next, we designed 5 personalized linear regression models in which 6 HRV parameters were input and the outcomes were 7 different stress degrees. Finally, we tested each model for 5min-long 16 segments individually. Consequently, the models could not hit the stress degrees exactly in some segments but the correlation coefficients between original stress pattern and estimated stress pattern during entire driving showed reasonably high.

• Korean Journal of Culture and Social Issue
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• v.18 no.3
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• pp.415-433
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• 2012

This study was conducted in order to explain the effect of driving behavior determinants such as drivers' personality and attitude that may induce risky driving behavior and to develop a valid method for discriminating risky drivers using the determinants. In the results of surveying 534 adult drivers, 5 driving behavior determinants (avoidance of problems, benefit/stimulus seeking, interpersonal anxiety, interpersonal anger, and aggression) were found to have a statistically significant effect on drivers' various risky driving behaviors. Using these factors, drivers were grouped according to risk levels (normal drivers, unintentionally risky drivers, and intentionally risky drivers). This result suggests that drivers' dangerous behavior level can be predicted using psychological factors such as their personality and attitude. Accordingly, if the driving behavior determinant model and the base score system used in this study are improved through further research, they are expected to be useful in predicting drivers' recklessness in advance, identifying problems, and providing differentiated safe driving education services based on the results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.603-604
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• 2011

자전거 운전은 본질적인 불안정한 시스템으로 자전거의 안전한 운전을 위해서는 지속적인 운전자의 상호작용으로 인하여 자전거의 안전성을 확보할 수 있다. 그것은 자전거의 운전이 운전자의 운동과 매우 밀접한 연관이 있다는 것을 알 수 있으며, 현재 자전거의 특성뿐 아니라 운전자의 운전에 대한 연구가 진행되고 있지만 정확한 자전거의 주행 안정성에 대하여 연구는 계속적으로 진행되고 있다. 본 논문에서는 자전거 운전자의 몸무게와 신장과 같은 사람의 인체 정보를 이용하여 적절한 안장 높이와 자전거 바퀴 사이의 거리 및 핸들의 높이를 조절할 수 있는 맞춤형 자전거 관리 시스템을 제시하고자 한다. 또한, 운전자 맞춤형 자전거의 설계는 실제 자전거 운전데이터와 영상데이터를 이용하여 적합한 자전거 모델을 제시하고 추출된 데이터를 통하여 분석된 결과를 제시하고자 한다.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.7-15
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• 2005

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.490-493
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• 2008

최근 텔레매틱스 기술은 운전자와 차량, 차량과 외부의 정보들을 이용하여 다른 산업과의 융합이 급속히 진행되고 있으며, 다양한 서비스에 대한 요구 역시 점차 증가하는 추세이다. 최근에는 차량의 위치 및 궤적 데이터 정보 서비스뿐만 아니라 차량을 통한 차별화된 고객별 영업, 마케팅 및 서비스 제공에 대한 VRM이 대두되고 있다. VRM은 차량의 주행 정보, 과거 이동정보, 운전자의 정보 등과 같은 차량에 관련된 다양한 정보에서 특정 규칙과 추출된 패턴 정보를 기반으로 영업, 서비스 생산, 마케팅 전략을 수립 및 적용할 수 있도록 해주는 것으로 CRM과 유사하다고 할 수 있다. 따라서 본 논문에서는 기존의 CRM의 성공 요인에 대한 선행 연구를 검토해 VRM의 전략적 관점에서 프로세스에 준거하여 고객자산가치관리와 VRM의 핵심기능인 고객자산가치 관리역량을 통해 차량의 주행정보, 차량 정검 정보, 운전자의 정보 등과 같은 차량에 관련된 모든 정보를 VRM 프레임워크가 갖추어야 할 요소를 도출하고 텔레매틱스 기반 VRM 프레임워크 모델을 제안해보고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1794-1795
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• 2015

현재의 자동차는 운전자에게 안정성과 편의성을 제공하기 위해서, 자동차 중심의 인터페이스를 넘어 인간 중심의 인간-차량 인터페이스로 발전함에 따라서 차량의 전체 시스템 설계에 영향을 미치는 새로운 양방향 인터페이스를 필요로 하고 있다. 운전자가 운전함에 있어 사용하고 있는 운전자의 음성, 신체 동작, 생체 신호와 차량의 주행 상태에 대한 종합적이고 체계적으로 관리가 기반이 되는 통합 모델을 통해서 지능화, 복합 체계화된 지능형 자동차를 효율적으로 구현할 수 있는 인간-차량 인터페이스를 제공할 것으로 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.97-106
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• 2003

When a route choice is done under uncertainty, a driver has some expectation of traffic conditions that will occur according to the route chosen. This study tries to build a framework in which we can observe the learning behavior of the drivers' expectations of the travel time under nonstationary environment. In order to investigate how drivers have their subjective expectations on traffic conditions in response to public information, a numerical experiment is carried out. We found that rational expectations(RE) formation about the route travel time can be expressed by the adaptive expectation model when the travel time changes in accordance with the nonstationary process which consists of permanent shock and transient shock. Also, we found that the adaptive parameter of the model converges to the fixed value corresponding to the route conditions.

• Journal of Power System Engineering
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• v.7 no.3
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• pp.61-68
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• 2003

Steering characteristics is an important factor in the evaluation of vehicle quality. To estimate steering characteristics in the vehicle conceptual design stage, vehicle dynamics simulation methods are very efficient. However, it is often difficult to simulate vehicle dynamics for the specific driving scenarios in open-loop driving environment. An efficient driver-in-the-loop vehicle model will be efficient for this job. A good tire model is also very important for the accurate vehicle dynamics simulation. In this research, a driver model is used to simulate vehicle steering dynamics for a 8-dof vehicle model with STI(Systems Technology, Inc.) tire model. For the demonstration of this model, a SUV(sports utility vehicle) and a sedan were simulated.