• 자동차안전학회지
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• 제15권4호
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• pp.23-31
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• 2023

In recent years, the technology for autonomous driving has been advancing rapidly, ADAS (Advanced Driver Assistance System) functions, which improve driver convenience and safety performance, are mostly equipped in recently released vehicles and range from level 0 to level 2 in autonomous driving technology. Among the various functions of ADAS, AEBS (Autonomous Emergency Braking System), which analyzes traffic accidents, is the most closely related to the vehicle's braking. This study developed a simulation technique for reproducing accidents related to AEBS based on real vehicle experimental data, and it was applied to the analysis of actual ADAS vehicle accidents to identify the causes of accidents.

• 인터넷정보학회논문지
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• 제24권1호
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Structural Engineering and Mechanics
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• 제74권1호
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• pp.19-32
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• 2020

Metallic energy-dissipation dampers are widely used in structures. They are comprised of an added damping and stiffness (ADAS) device with many parallel, diamond-shaped hole plates, the neck width of which is an important parameter. However, no studies have analyzed the neck width's influence on the ADAS device's performance. This study aims to better understand that influence by conducting a pseudo-static test on ADAS, with three different neck widths, and performing finite element analysis (FEA) models. Based on the FEA results and mechanical theory, a design neck width range was proposed. The results showed that when the neck width was within the specified range, the diamond-shaped hole plate achieved an ideal yield state with minimal stress concentration, where the ADAS had an optimal energy dissipation performance and the brittle shear fracture on the neck was avoided. The theoretical values of the ADAS yield loads were in good agreement with the test values. While the theoretical value of the elastic stiffness was lower than the test value, the discrepancy could be reduced with the proposed modified coefficient.

• 전기전자학회논문지
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• 제22권4호
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• pp.970-977
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• 2018

자율 주행 차량은 주변 환경의 정보를 수집하는 센서, 측정된 데이터를 판단하는 제어 모듈로 구성된 첨단 운전자 지원 시스템(ADAS)을 기반하고 있다. 최근에 자율주행 기술에 대한 관심이 증가함에 따라 ADAS 입문 개발자들 및 학습자들을 위한 손쉬운 개발프레임워크가 필요하다. 그러나, 기존 개발 및 검증 방식은 고성능 자동차 시뮬레이터를 기반하기 때문에 검증 방법의 복잡성 및 고비용 등의 단점이 있다. 또한, 대부분의 방식은 시뮬레이터로부터 ADAS에서 필요로 하는 센싱 데이터를 직접 제공하지 않으므로 검증 신뢰성의 한계가 있다. 본 논문에서는 기존 방식들의 문제점들을 극복하는 3D 자동차 시뮬레이터를 활용한 상호작용형 ADAS 개발 및 검증 프레임워크를 제시한다. 영상인지 기반의 인공지능을 적용한 ADAS를 3D 자동차 시뮬레이터에서의 가상센서로 구현하고, 실제 시나리오에 자율주행 검증을 진행하였다.

• 한국ITS학회 논문지
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• 제18권6호
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• pp.110-123
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• 2019

교통 데이터는 교통계획이나 교통시스템 운영에 필요한 기초 자료이며 최근 ADAS 카메라로 측정한 선행 차량과의 거리를 이용하여 교통류를 파악하는 방법이 시도되고 있다. 본 연구는 영상기반 차량인식의 거리오차를 반영한 미시적 시뮬레이션 분석을 통해 교통류를 추정하기 위한 ADAS 차량의 활용 가능성을 살펴보았다. 차로수, 교통수요, 프로브 차량의 점유율(MPR), 시공간 검지영역 등에 따른 교통류 추정치의 표준 평균 제곱근 오차를 통해 분석을 수행하였다. 분석결과, ADAS 카메라의 최대 인식거리의 한계로 저밀도 교통류(LOS A, LOS B)의 추정치는 신뢰할 수 없는 수준이다. 다차로나 교통수요가 크고 점유율(MPR)이 높을 경우 추정치의 신뢰성이 개선될 수 있지만, 인위적으로 점유율(MPR)을 높이는 것은 현실적으로 어려움이 있다. 또한, 검지영역의 시간범위를 연장함으로써 추정치의 신뢰성을 개선할 수 있지만, 가장 크게 영향을 미치는 것은 ADAS 차량의 주행행태로서 해당 차량이 도로의 교통류와 상이한 주행행태를 보일 경우 그 추정치는 신뢰할 수 없게 된다. 결론적으로 모든 교통류를 정확히 추정하지는 못 하지만 ADAS 카메라의 성능이나 기능을 개선함으로써 ADAS 차량의 활용 가능성은 확대될 것이다.

• 대한인간공학회지
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• 제36권2호
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• pp.87-108
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• 2017

Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

• 한국ITS학회 논문지
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• 제19권6호
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• pp.208-221
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• 2020

본 연구는 첨단운전자보조시스템(Advanced Driver Assistance System, ADAS)이 빠르게 보급됨에 따라 표본 프로브 차량에 설치된 ADAS로부터 얻은 개별차량의 궤적 데이터와 전방차량과의 차두거리 데이터를 이용하여 연속류의 교통밀도를 추정 및 분석하는 것을 목적으로 한다. 과거 연속류 교통밀도는 주로 차량검지시스템(Vehicle Detection System, VDS)에서 수집되는 교통량, 속도, 점유율 등의 데이터를 가공하여 추정되거나, CCTV등의 영상정보를 활용하여 직접 차량 대수를 계수하여 추정되었다. 이러한 방식은 교통밀도 추정의 공간적 제약이 있고, 교통 혼잡시 추정의 신뢰도가 낮다는 한계를 보였다. 이에 본 연구에서는 선행연구의 한계를 극복하기 위해 ADAS로부터 수집된 개별차량 궤적 데이터와 차두거리 정보를 활용하여 도로의 공간을 검지하고 일반화된 밀도(Generalized Density)방식을 이용하여 시공간적 교통밀도를 추정한다. 이에 따라 ADAS차량의 표본율에 따른 교통밀도 추정의 정확도를 분석한 결과, 30%의 표본율일 경우 교통밀도 참 값과 약 90% 일치하는 것으로 나타났다. 이를 통해 본 연구는 향후 ADAS 및 자율주행차량이 혼재되는 도로 상황에서 신뢰도 높은 교통밀도 추정을 가능하게 하며 효율적인 교통운영관리에 기여할 수 있을 것으로 판단된다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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• pp.7-13
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• 2020

We describes V2X technology, a connectivity-based recognition technology that is attracting attention as a key technology for implementing autonomous driving technology, and autonomous communication modules that implement ADAS technology, a sensor-based recognition technology. It also explains the trends in V2X technology standardization centered on IEEE 802.11p, which is a WAVE technology standard based on Wi-Fi/DSRC. Finally, we will discuss the market growth trend of V2X communication modules in the United States, the leading V2X technology module, and the development of technology development trends of major domestic and international companies that are leading the global technology market related to V2X communication modules. V2X and ADAS technologies will be the biggest influence on automotive purchasing decisions. In recent years, V2I mandates have been promoted beyond V2V, mainly in developed countries such as the United States. The related industry needs to focus on the development of information transmission network technology that can support high frequency high efficiency(transmission rate) and sophisticated positioning accuracy beyond conventional vehicle communication.

• 자동차안전학회지
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• 제11권4호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.637-639
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• 2021

자율주행 연구가 활발히 진행되면서 ADAS(Advanced Driver Assistance System)에서 차량의 위치를 파악하고 경로를 유지하는데 차선 검출은 필수적인 기술이다. 차선 검출은 허프 변환과 RANSAC(Random Sample Consensus)과 같은 영상처리 알고리즘을 이용하여 검출한다. 본 논문은 라즈베리파이3 B+에 OpenCV를 이용하여 선형 도형 검출 알고리즘을 구현하고 있다. OpenCV 가우시안 블러 구조와 캐니 에지 검출을 통해 문턱값을 설정하였고, 선형 검출 알고리즘을 통한 차선 인식에 성공하였다.