• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.123-132
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• 2017

Traffic lights contain very important information for safety driving. So, the delivery of the information to drivers in real-time is a very critical issue for advanced driver assistance systems. However, traffic light detection is quite difficult because of the small sized traffic lights and the occlusion in real world. In this paper, a traffic light detection method using modified color based saliency map and morphological information is proposed. It shows 98.14% of precisions and 83.52% of recalls on computer simulations.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.33-38
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• 2015

In a V2X convergence service environment, the principal service among infotainment services and driver management services must be supported centering on critical information of the driver, maintenance manager, customer, and anonymous user. Many software applications have considered solutions to be satisfied the specific requirements of driving care programs, and plans. This paper describes data flow diagram of a secure clinic system for driving car diagnosis, which is included in clinic configuration, clinic, clinic page, membership, clinic request processing, driver profile data, clinic membership data, and clinic authentication in the V2X convergence service environment. It is reviewed focusing on security threat issue of ITS diagnostic system such as spoofing, tampering, repudiation, disclosure, denial of service, and privilege out of STRIDE model.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.280-283
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• 2013

최근 원자력 발전소, 의료 시스템, 항공 시스템 등과 같이 사람의 생명과 밀접하게 관련되어 있는 소프트웨어로 제어하는 시스템들이 점차 늘어나고 있다. 차량에서 또한 차량 제어 소프트웨어의 오작동으로 인한 잦은 사고로 인하여 운전자와 탑승자의 생명을 위협 받고 있다. 이러한 문제로 인하여 차량시스템 제어 소프트웨어도 안전성 확보를 위한 기술로 차량에 통신 기술을 접목한 차량 통신 기술에 대한 관심이 높아지고 있다. 차량 운전자 뿐 아니라 탑승자의 안전과 밀접하기 때문에 많은 연구가 진행되고 있다. 이러한 많은 연구 중 긴급메시지전송 시스템은 차량 간 통신(V2V)을 통한 운전자의 안전성 확보에 대한 연구다. 본 논문에서는 차량 긴급메시지 전송에 필요한 모듈을 구조적으로 나누고 이를 통하여 긴급메시지 전송시스템 구조의 안전성을 평가한다. 긴급메시지 전송시스템의 안정성을 검증하기 위하여 오토마타 모델링을 통한 시스템 구조를 설계하고 검증을 위해 CTL 논리식 정의, SMV(Symbolic Model Verifier)검증도구를 통한 시스템 안전성 모델 검사를 하였다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.240-243
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• 2002

본 연구에서는 인간공학적 평가를 위한 한국인 인체모델을 개발하고, 인체 모델의 평가를 위해 팔 동작의 시뮬레이션 및 리치 평가를 수행하였다. 한국인의 인체측정자료를 이용하여 통계학적 분석을 실시하고, 인체 자료생성 프로그램을 통해 인체 각 지체들의 특성치와 상관관계를 얻었다. 이를 바탕으로 인체 모델을 구성하고 가상 공간에서의 용이한 적용을 위해 인체 모델은 3차원 그래픽 기술을 통해 가시화되었다. 차량모델과 인체모델을 통합하고 차량 내에서 운전자의 팔 동작 표현 및 리치 평가기능을 구현하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.699-705
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• 2012

The role of a seat belt in a vehicle is to protect the driver from injury when a crash occurs. However when a large crash occurs, the driver slips forward and receives a strong impact. To prevent this situation, improvement of seat belts is essential. In this study, the new concept of a dynamic locking tongue (DLT) for seat belts is developed. The DLT device is used to reduce the impact to the driver's chest by tightening the webbing, so the driver is protected from severe injury in a large crash. First, a finite element model of the DLT device is created using SAMCEF and structural analysis is conducted with boundary conditions similar to those found in experiments. Then, the stress in the DLT device can be calculated. Second, the shape of the DLT device is optimized using the response surface analysis method in order to minimize the stress and weight. The validity of the optimization of the DLT device is verified using structural analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.175-182
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• 2010

The paper presents a novel algorithm for face and iris detection with the application for driver iris monitoring. The proposed algorithm consists of the following major steps: Skin-color segmentation, facial features segmentation, and iris positioning. For the skin-segmentation we applied a multi-layer perceptron to approximate the statistical probability of certain skin-colors, and filter out those with low probabilities. The next step segments the face region into the following categories: eye, mouth, eye brow, and remaining facial regions. For this purpose we propose a novel segmentation technique based on estimation of facial class probability density functions (PDF). Each facial class PDF is estimated on the basis of salient features extracted from a corresponding facial image region. Then pixels are classified according to the highest probability selected from four estimated PDFs. The final step applies the circular Hough transform to the detected eye regions to extract the position and radius of the iris. We tested our system on two data sets. The first one is obtained from the Web and contains faces under different illuminations. The second dataset was collected by us. It contains images obtained from video sequences recorded by a CCD camera while a driver was driving a car. The experimental results are presented, showing high detection rates.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.41-51
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• 2010

In the research for driver assistance systems, traffic sign information to the driver must be a very important information. Therefore, the detection system of traffic signs located on the road should be able to handel real-time. To detect the traffic signs, color and shape of traffic signs is to use the information after images obtained using the CCD camera. In the road environment, however, using color information to detect traffic sings will cause many problems due to changes of weather and environmental factors. In this paper, to solve it, the candidate traffic sign regions are detected from road images obtained in a variety of the illumination changes using the HSI eign-color model. And then, using the invariant moment-based SVM classifier to detect traffic signs are proposed. Experimental results show that, traffic sign detection rate is 91%, and the processing time per frame is 0.38sec. Proposed method is useful for real-time intelligent traffic guidance systems can be applied.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.176-190
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• 2002

According as vehicles increases, system such as Advanced Drivers Assistance System(ADAS ) to inform forward situation to driver is required. In this paper, we proposes method to detect forward vehicles and lane from sequential color images by basis process to inform forward situation to driver. We detect a front vehicle using that shadow area exists on part under vehicles and that road area occupies many parts even if road traffic is confused. We detect lane information using that lane part is white order by reverse characteristic of shadow area. This method shows good result in case road is confused or there is direction indication to road. HSV color space is selected for color modeling. This method uses saturation component and value component in HSV color model to detect vehicles and lane. It uses statistics features of HSV component and position to know whether detected vehicles area is vehicles such as vehicles previous frame. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and Present the results such as processing time, accuracy and vehicles detection against the images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.238-241
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• 2019

In this paper, a "Vehicle Analysis System(VAS) using cloud and data mining" is proposed that store all the sensor data measured in the vehicle in the cloud, analyze the stored data using the classification model, and provide the analyzed data in real time to the driver's display. The VAS consists of two modules. First, Sensor Data Communication Module(SDCM) stores the sensor data measured in the vehicle in a table of the cloud server and transfers the stored data to the analysis module. Second, Sensor Data Analysis Module(SDAM) analyzes the received data using the genetic algorithm and provides analyzed result to the driver in real time. The VAS stores sensor data collected in the vehicle in the cloud server without accumulating it in the vehicle, and stored data is analyzed in the cloud server, so that the sensor data can be quickly and efficiently managed without overloading the vehicle. In addition, the information desired by the driver can be visualized on the display, thereby increasing the stability of the autonomous vehicle.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.423-432
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• 2022

This paper addresses the safety concern that the SOH of batteries in electric vehicles decreases sharply when drivers change or their driving patterns change. Such a change can overload the battery, reduce the battery life, and induce safety issues. This paper aims to present the SOH as the changes on a dashboard of an electric vehicle in real-time in response to user pattern changes. As part of the training process I used battery data among the datasets provided by NASA, and built models incorporating linear regression and ARIMA, and predicted new battery data that contained user changes based on previously trained models. Therefore, as a result of the prediction, the linear regression is better at predicting some changes in SOH based on the user's pattern change if we have more battery datasets with a wide range of independent values. The ARIMA model can be used if we only have battery datasets with SOH data.