• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.98-105
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• 2007

In this paper, we propose the method and system which determines the condition for safe and unsafe lane changing. To determine the condition, first, the system sets up the Region of Interest(ROI) on the neighboring lane. Second, a dangerous vehicle is extracted during the line changing. Third, the condition is determined to wm or not by calculating the moving direction, relative distance md relative velocity. To set up the ROI, the only one side lane is detected and the interested region is expanded. Using the coordinate transformation method, the accuracy of the ROI raised. To correctly extract the vehicle on the neighboring lane, the Adaptive Background Update method and Image Segmentation method which uses the feature of the travelling road are used. The object which is extracted by the dangerous vehicle is calculated the relative distance, the relative velocity and the moving average. And then in order to ring, the direction of the vehicle and the condition for safe and unsafe is determined. As minimizes the interested region and uses the feature of the travelling road, the computational quantity is reduced and the accuracy is raised and a stable result on a travelling road images which demands a high speed calculation is showed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.193-194
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• 2022

자율운항선박은 제4차 산업혁명 시대의 핵심기술인 사물인터넷과 빅데이터, 인공지능 등이 집약된 미래 고부가가치 선박으로 주목받고 있는 반면, 실제 선박 운항 중 많은 위험요소들로 선박 안전상의 우려가 제기되고 있다. 해양교통에 있어 안전규제는 해사안전 증진 및 해양사고 위험성을 최소화하기 위한 중요요소라고 할 수 있으며, 자율운항선박 시대에서도 동일하게 작용할 것으로 보인다. 이에 자율운항선박 시대 준비를 위한 안전규제의 재정립은 선박의 안전운항을 위한 안전관리체계 정비를 위한 핵심사항이라고 할 수 있으며. 최근 국내·외에서 논의되고 있는 자율운항선박 운항을 위한 규제 개발 역시 중요한 의미를 가진다. 본 논문에서는 자율운항선박 운용을 위한 안전규제체계 개선을 위해 실제 상용화를 앞둔 자율주행자동차 안전위험 이슈 분석 사례를 기반으로 자율운항선박 운용에 따른 안전위험 이슈를 도출했다. 이러한 결과는 자율운항선박의 운용을 위한 규제 개발 논의 시점에서 향후 자율운항선박의 상용화 및 안전규제체계 마련을 위한 기초자료로 활용 할 수 있을 것으로 기대된다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.251-261
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• 2019

The importance of autonomous driving systems that utilize V2X services such as V2V(Vehicle to Vehicle) and V2I(Vehicle to Infrastructure) for safer and more comfortable driving is increasing with the recent development of autonomous vehicles. Partly autonomous vehicles based on environmental sensors have limitations for predicting and determining areas beyond the recognition distance of the mounted sensors and in response to atypical objects that are difficult to detect. Therefore, it is important to utilize the V2X service to improve the limit of sensor detection performance and to make driving safer and more comfortable. However, there may be an accident risk of autonomous vehicles due to incorrect information provided by V2X. Thus, the application of technology to prevent this needs to be considered. In this pater, we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to derive the risk sources of autonomous vehicles due to V2I malfunctions by using the communication between vehicles and infrastructure among V2X. We also developed ASIL ratings based on the simulations and real vehicle tests of the malfunctions of major cases of usnig V2I.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.17-26
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• 2010

This study presents a decision making process for installation of wind barrier which is used to reduce the wind acting on running vehicle on expressway. At the first stage of this study, the lateral deviations of running vehicles under side winds were computed from the commercial softwares, CarSim and TruckSim, and then the critical wind speeds for car accident were evaluated from predefined risk index. To determine whether it is needed to install wind barrier or not, cost and benefit from wind barrier are calculated during lifetime. In obtaining car accidental risk, probabilistic distribution of wind speed, daily traffic volume, mixture ratio in the volume, and duration time for wind speed range are considered. It is recommended to install wind barrier if benefit from the barrier installation exceed construction cost. In the numerical examples, case studies were shown for risk and benefit calculation and main risky regions on Korean highway were all evaluated to identify the number of installation sites.

• Annual Conference of KIPS
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• 2018.05a
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• pp.394-397
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• 2018

최근 인공지능 연구가 활발하게 진행이 되면서 여러 기업에서 자율 주행연구도 활발하게 진행되고 있다. 하지만 실제 상황에서 자동차 주행 데이터를 얻기에는 여러 위험사항들과 경제적인 낭비가 있다. 그렇기 때문에 게임 상에서 데이터를 수집하고 딥러닝을 이용해 학습을 하기로 했다. 본 논문에서는 실제 세계와 유사한 환경을 가지고 있는 자동차 게임을 이용하여 자율 주행을 시도 했다. 자율 주행 시 많이 쓰이는 End to End 방법으로 데이터를 수집하면 두 가지 데이터가 저장된다. 하나는 이미지 데이터고 두 번째는 방향키 데이터다. 이러한 데이터들을 numpy 타입으로 40분간 데이터를 수집한 후 딥러닝에 많이 쓰이는 tensorflow를 사용하여 구현한 CNN을 이용하여 학습이 되는 것을 확인을 하고 91.9%의 정확도를 얻었다. 이를 기반으로 실세계에서의 사용 가능성을 확인했다.

• Annual Conference of KIPS
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• 2023.05a
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• pp.116-118
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• 2023

자율주행차가 제공하는 새로운 시장과 경쟁력, 인력 및 시간 절약, 교통 체증 문제 해결 등의 장점을 다루고, UN 사이버 보안 법률에 따른 자율주행차의 기술적인 요구사항을 준수해야 한다. 하지만 자율주행차에 대한 기술적인 요구사항을 준수하는 것으로는 모든 사이버 공격에 대해서 막을 수 없다. 자율주행차의 법적 요구사항과 사이버 보안 위협에 대처하는 방법을 다룬다. 특히 RTOS(Real Time OS)와 같은 실시간 시스템에 매우 위험할 수 있는 DRAM(Dynamic Random Access Memory)에 대한 로우해머링 공격 기법에 대해 분석하고 로우해머링에 대한 보안 방법을 제시한다. 그리고 자율 주행 시스템의 안전과 신뢰성을 보장하기 위해 하드웨어 기반 또는 소프트웨어 기반 방어 기술을 소개하고 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Journal of Platform Technology
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• v.11 no.3
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• pp.24-31
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• 2023

Recently, interest in UAM (Urban Air Mobility, UAM), which can take off and land vertically in the operation of urban air transportation systems, has been increasing. Therefore, various start-up companies are developing related technologies as eco-friendly future transportation with advanced technology. However, studies on ways to increase safety in the operation of UAM are still insignificant. In particular, efforts are more urgent to improve the safety of risks generated in the process of attempting to land in the city center by UAM equipped with autonomous driving. Accordingly, this study proposes a plan to safely land by avoiding dangerous region that interfere when autonomous UAM attempts to land in the city center. To this end, first, the latitude and longitude coordinate values of dangerous objects observed by the sense of the UAM are calculated. Based on this, we proposed to convert the coordinates of the distorted planar image from the 3D image to latitude and longitude and then use the calculated latitude and longitude to compare the pre-learned feature descriptor with the HOG (Histogram of Oriented Gradients, HOG) feature descriptor to extract the dangerous Region. Although the dangerous region could not be completely extracted, generally satisfactory results were obtained. Accordingly, the proposed research method reduces the enormous cost of selecting a take-off and landing site for UAM equipped with autonomous driving technology and contribute to basic measures to reduce risk increase safety when attempting to land in complex environments such as urban areas.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.287-300
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• 2021

Collaborative Cyber-Physical Systems (CCPS) are those systems that contain tightly coupled physical and cyber components, massively interconnected subsystems, and collaborate to achieve a common goal. The safety of a single Cyber-Physical System (CPS) can be achieved by following the safety standards such as ISO 26262 and IEC 61508 or by applying hazard analysis techniques. However, due to the complex, highly interconnected, heterogeneous, and collaborative nature of CCPS, a fault in one CPS's components can trigger many other faults in other collaborating CPSs. Therefore, a safety assurance technique based on fault criticality analysis would require to ensure safety in CCPS. This paper presents a Fault Criticality Matrix (FCM) implemented in our tool called CPSTracer, which contains several data such as identified fault, fault criticality, safety guard, etc. The proposed FCM is based on composite hazard analysis and content-based relationships among the hazard analysis artifacts, and ensures that the safety guard controls the identified faults at design time; thus, we can effectively manage and control the fault at the design phase to ensure the safe development of CPSs. To justify our approach, we introduce a case study on the Platooning system (a collaborative CPS). We perform the criticality analysis of the Platooning system using FCM in our developed tool. After the detailed fault criticality analysis, we investigate the results to check the appropriateness and effectiveness with two research questions. Also, by performing simulation for the Platooning, we showed that the rate of collision of the Platooning system without using FCM was quite high as compared to the rate of collisions of the system after analyzing the fault criticality using FCM.