• 한국ITS학회 논문지
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• 제17권6호
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• pp.84-95
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• 2018

자율주행 과실 여부 판단 위한 방법으로 수학적인 모형인 responsibility-sensitive safety(RSS)를 제시된 이후로 자율주행 관련 산업으로부터 많은 관심을 받고 있다. 하지만, 이러한 수학적 모형이 자율주행자동차가 관련된 교통사고 발생 시 책임소재를 명확히 하는 데 활용될 수 있는 지에 대한 종합적인 검토는 부족한 실정이다. 본 연구에서는 RSS 모형의 적용성과 활용을 위해서 추가적으로 해결되어야 할 사항에 대하여 분석하였다. 결론적으로 RSS 모형을 활용하기에는 모형식 자체 및 수용성 등에 한계가 있으며, RSS 모형을 실무적으로 사용하려고 한다면 자율주행자동차의 반응시간을 정의하고, 자율주행자동차별로 적절한 기술수준에 따라서 반응시간 값을 측정하고 관리할 필요가 있는 것으로 판단된다.

• 한국정보처리학회논문지
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• 제3권5호
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• pp.1037-1045
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• 1996

본 논문은 전방차량 추적에 있어서 스테레오 카메라 패러렐 모델을 사용하여 전방 차량과의 거리 및 헤딩앵글 데이터를 추출하고 이들 데이터를 이용하여 무인자동차 ART(Binocular Autonomous Research Team vehicle)를 제어하는 방법에 관한 것이다. 무인자동창의 제어는 2개의 역전달 뉴럴네트워크의 일종인 TDNN(Time De-lay Neural Network)을 각각 독립적으로 사용하였다. 그중 하나는 S-TDNN으로 추적차량의 속도와 전방차량과의 거리를 제어하며, 다른 하나는 A-TDNN으로 무인차량의 스티어링 앵글을 전담 제어한다. 인간 운전자가 전방차량을 추적하면서 수집한 제이터를 이용하여 상기 뉴럴네트워크를 학습시키며, 학습된 뉴럴네트워크는 인간이 운전하였을 때와 같은 조건하에서 전방차량의 추적을 만족스럽게 수행하였다. 뉴럴네트워크를 이용한 제어프 로그램은 이식성이 높아 다른 종류의 차량에도 쉽게 적용할 수 있어 타모델에 적용 시에 개발경비와 소요 시간을 줄일 수 있는 장점이 있다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권3호
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• 자동차안전학회지
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• 제15권1호
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• pp.35-44
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• 2023

The purpose of this study is to predict how the actual accident changes by reconstructing the accident with an Autonomous Emergency Braking system (AEB) based on the actual accident of the LTAP-OD (Left Turn Crossing Path - Opponent Direction) intersection. A virtual AEB sensor was developed, and 150 head-on collision accident reports were secured to the insurance company to reconstruct the accident. As a result of the accident type analysis, a total of 13 types of head-on collision accidents were derived, and it is the LTAP-OD intersection accident with the highest frequency. In the LTAP-OD intersection accident, the simulation was conducted by applying the virtual AEB of each vehicle, the accident rate decreased by 90% or more when the AEB of the left-turn vehicle was applied, and the accident rate decreased by 50%. In addition, the most frequent collision types in LTAP-OD accidents were the front bumper on the driver's side of a vehicle going straight and the front bumper on the passenger's side of a vehicle turning left.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1460-1463
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• 2005

In this paper, analysis of magnetic marker for autonomous vehicle guidance system using 3-axis magnetic sensor propose. Position sensing is an important an estimation system of vehicle position and orientation on magnetic lane, which is a parameter of the steering controller for automated lane following is described. To verify that the magnetic dipole model could be applied to a magnetic unit paved in roadway, the analysis of the data 3-axis magnetic field measured experimentally.

• 제어로봇시스템학회논문지
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• 제22권5호
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• pp.339-345
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• 2016

This paper presents a robust speed control of an autonomous vehicle using a disturbance observer. For the purpose, the transfer function of speed dynamics of an autonomous vehicle is identified using step response data. Based on the identified transfer function, model based PID (Proportional-Integral-Derivative) control is designed. In order to design a robust control against load variations on the vehicle, a disturbance observer (DOB) based control is devised. The performance of the designed DOB based control is demonstrated by real experiments.

• 한국자동차공학회논문집
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• 제15권3호
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• pp.1-9
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• 2007

A major concern for Autonomous Military Robot in the rough terrain is the problem of moving robot from an initial configuration to goal configuration. In this paper, We generate a local path to looking for the best route to move an goal configuration while avoiding known obstacle from world model, not violating the mobility constraints of robot. Trough a Simulator for Unmanned Autonomous Vehicle, We can simulate a traversability of unmanned autonomous vehicle based on steering, acceleration, braking command obtained from local path planning.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.263-272
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• 2021

At a time when securing driving safety is the most important in the development and commercialization of autonomous vehicles, AI and big data-based algorithms are being studied to enhance and optimize the recognition and detection performance of various static and dynamic vehicles. However, there are many research cases to recognize it as the same vehicle by utilizing the unique advantages of radar and cameras, but they do not use deep learning image processing technology or detect only short distances as the same target due to radar performance problems. Radars can recognize vehicles without errors in situations such as night and fog, but it is not accurate even if the type of object is determined through RCS values, so accurate classification of the object through images such as cameras is required. Therefore, we propose a fusion-based vehicle recognition method that configures data sets that can be collected by radar device and camera device, calculates errors in the data sets, and recognizes them as the same target.

• 자동차안전학회지
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• 제15권2호
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• pp.28-34
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• 2023

The Republic of Korea aims to complete the commercialisation of Level 4+ cooperative autonomous driving in 2027. It also plans to include V2X OBU in the K-NCAP evaluation items. Therefore, communication performance safety evaluation criteria for V2X OBU need to be established, and an OBU with necessary functions is needed to develop V2X communication performance safety evaluation technology for vehicles. In this study, we implemented a V2X OBU control board prototype that can be used to develop a V2X communication performance safety evaluation technology for Level 4+ autonomous vehicles, and confirmed that the control board prototype works normally.

• 자동차안전학회지
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• 제15권4호
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• pp.48-57
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• 2023

With the advance of autonomous vehicle technology various sitting posture is possible like relax position (inclined seating posture). Parametric study was done with MADYMO, a mutibody dynamics solver, to investigate the effect of sitting posture in different frontal crash modes, full frontal, 40% offset, and angled rigid barrier crash as well as various impact speeds. Hybrid III 50th male and 5th female dummies were used to figure out the difference induced by occupant weight and dimension. Restraint system parameters complying to current safety protocols like NCAP are studied if they still work effectively in relax position which is feasible with autonomous vehicles.