• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.9-23
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• 2015

A lane change maneuver which has a high driver cognitive workload and skills sometimes leads to severe traffic accidents. In this study, the Advanced Lane Change Assist System (ALCAS) was developed to assist with the automatic lane changes in merging sections which is mainly based on an automatic control algorithm for detecting an available gap, determining the Optimal Lane Change Start Point (OLCSP) in various traffic conditions, and positioning the merging vehicle at the OLCSP safely by longitudinal automatic controlling. The analysis of lane change behavior and modeling of fundamental lane change feature were performed for determining the default parameters and the boundary conditions of the algorithm. The algorithm was composed of six steps with closed-loop. In order to confirm the algorithm performance, numerical scenario tests were performed in various surrounding vehicles conditions. Moreover, feasibility of the developed system was verified in microscopic traffic simulation(VISSIM 5.3 version). The results showed that merging vehicles using the system had a tendency to find the OLCSP readily and precisely, so improved merging performance was observed when the system was applied. The system is also effective even during increases in vehicle volume of the mainline.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.65-69
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• 1998

고속 주행중인 자동차 환경에서 운전자의 안전 및 편의성을 위하여, 음성인식 기술을 이용한 각종 차량 편의장치를 제어하는 것으로, 운전자와 자동차와의 Man Machine Interface 구조로 구성되었다. 이 시스템은 주행중인 자동차 환경에서 보조적인 스위치의 조작없이 상시 음성의 입, 출력이 가능하도록 하며, band pass filter를 이용하여 잡음 환경에 강인한 모델을 선택하도록 하였으며, 음성의 특징 파라미터와 인식 알고리즘은 perceptual linear predictive 13차와 one-stage dynamic programming을 사용하였다. off-line 실험 결과 고속 주행중인 자동차 환경에서 자주 사용하는 차량제어 명령 33개에 대하여 화자독립 82.47%(중부고속도로), 화자종속 94.44%의 인식율을 구하였다. 또한 고속 주행중인 차량에서 kvhs, 핸드폰 사용으로 인한 사고를 줄이기 위하여 음성으로 전화를 걸 수 있도록 하는 Voice Dialing기능도 구현하였다.

• Journal of Auto-vehicle Safety Association
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• v.11 no.4
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• pp.39-49
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• 2019

Autonomous vehicle is a car which drives itself without any human interaction. SAE provides technical definitions for autonomous and international standards for test evaluation. Accordingly, automobile industry is actively researching development and evaluation of various ADAS (Advanced Driver Assistance Systems), : representative technology of autonomous technology. Recently, ADAS is in the commercialization level such as ACC, LKAS, AEB, and HDA etc. And it also has issues about safety evaluation. The purpose of HDA in ADAS is reduced the driving load on highway. It has a function which can maintain lane keeping and control distance from forward vehicle. This function is evaluated to be useful for accident prevention. Therefore, this paper proposes the safety evaluation scenario of HDA, considering the domestic highway design criteria and the situation that may arise on the actual highway. We compared and analyzed the data acquired through simulation and actual vehicle test. And verified the reliability of the proposed safety evaluation scenario. The verified result is expected safety evaluation of HDA is possible even under the bad condition, which cannot be tested.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.205-209
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• 2008

Recently, for development of hardware systems, it has been comercially developed for lane detection system of assistive funtion to drivers. There are so many driving systems that is capable of detecting lane for ideal environment like quite visible lane and sweep curve just like highway, but these kinds of system are hard to apply for self driving system because it is difficult to detect lane in dynamic environment, which have rapid curve or only one sided lane For this paper, we proposed intelligent driving system that is able to detect the lane in case of rapid curve by labeling, or one sided lane by lane prediction. based on experimental results, we prove our lane detection system is able to detect lane not only in ideal environment, but also environment which have rapid curve or one sided lane.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.68-80
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• 2016

This study proposes the traffic prediction and optimal traffic control system based on cell transmission model and genetic algorithm in cloud environment. The proposed prediction and control system consists of four parts. 1) Data preprocessing module detects and imputes the corrupted data and missing data points. 2) Data-driven traffic prediction module predicts the future traffic state using Multi-level K-Nearest Neighbor (MK-NN) Algorithm with stored historical data in SQL database. 3) Online traffic simulation module simulates the future traffic state in various situations including accident, road work, and extreme weather condition with predicted traffic data by MK-NN. 4) Optimal road control module produces the control strategy for large road network with cell transmission model and genetic algorithm. The results show that proposed system can effectively reduce the Vehicle Hours Traveled upto 60%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.951-960
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• 2006

Structural pavement analysis considering lateral loads of moving vehicle was carried out in order to simulate passing vehicle loads under various interface conditions. To verify of existing multi-layer elastic analysis of layer interface effect parameters, this study compared outputs by using ABAQUS, a three dimensional finite element program and KENLAYER, multi-layer elastic analysis as vertical load was applied to the surface of asphalt pavements. Pavement performance depending on interface conditions was quantitatively evaluated and fundamental study of layer interface effect parameters was performed in this study. As results of the study, if only vertical loads of moving vehicle is applied, subdivision of either fully bonded or fully unbonded is enough to indicate interface effect parameters. On the other hand, when lateral loads are applied with vertical loads, pavement behavior and performance are greatly changed with respect to layer interface conditions. The thinner thickness of the asphalt layer is and the smaller elastic moduli of the asphalt layer is, the more pavement behavior is influenced by interface conditions. In addition, regression analysis equation analytically computing tensile strain which was considered thicknesses and elastic moduli of the asphalt layer and layer interface effect parameters at the bottom of the asphalt layer was presented using database from numerical analyses on national pavement model sections.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.