• 자동차안전학회지
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• 제14권1호
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• pp.6-13
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• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• 자동차안전학회지
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• 제10권1호
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• pp.32-37
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• 2018

This paper proposes autonomous speed control strategy for an Electric Vehicle on urban road. SNU campus road is used to reperesent urban road situation. Motor efficiency of driving on campus circulation road can be improved by controlling velocity properly. Given information of campus road, especially slope of road, acceleration is selected from candidate, considering consumed power, human factor and driving time. To apply urban situation, preceding vehicle is also considered. With preceding vehicle, acceleration is defined according to clearance and relative velocity. Acceleration is bounded in normal range. Proposed acceleration control method is activated with proper velocity range for campus circulation road. With acceleration control, motor efficiency becomes better than driving with constant vehicle. To evaluate the performance of proposed acceleration controller, simulation study is conducted via MATLAB.

• 자동차안전학회지
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• 제12권2호
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• pp.14-20
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• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• 대한기계학회논문집A
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• 제41권7호
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• pp.575-583
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• 2017

본 논문에서는 고속도로의 합류지점 상황에서 자율주행을 위한 운전 모드 결정 알고리즘의 개발 및 평가를 진행하였다. 합류 상황을 위한 자율주행 알고리즘 개발에 있어 적절하게 합류를 결정하는 운전 모드 결정이 필수적이다. 운전자 모드는 총 2가지로 차선 유지, 차선 변경(합류)이다. 합류 모드 결정은 주변 차량의 정보 및 합류 차선에 남은 거리를 기반으로 결정된다. 합류 모드 결정 알고리즘에서는 합류 가능 여부를 판단하고 합류가 가능할 때, 안전하고 빠르게 합류하기 위한 최적의 위치를 찾는다. 안전 주행 영역은 주변 차량의 정보 및 주행 모드를 기반으로 정의된다. 안전 주행 영역으로 자율주행 차량을 유지하기 위한 조향각과 종방향 가속도를 얻기 위해 여러 제한 조건이 더해진 강건 모델 예측기법이 사용되었다. 본 논문에서 제안된 알고리즘은 컴퓨터 시뮬레이션을 이용해 검증되었다.

• 한국항행학회논문지
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• 제22권5호
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• pp.391-399
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• 2018

V2X 통신이란 차량이 유무선망을 통해 다른 차량, 인프라, 네트워크, 보행자 등과 같은 객체들과 정보를 교환하는 기술이다. V2X 통신 기술은 최근 꾸준히 연구되어 왔으며 자율주행 차량 기술과 결합된 자율협력주행 기술에 중요한 역할을 수행해왔다. 자율주행 차량은 V2X 통신을 통해 외부 정보를 수신함으로써 차량 센서의 인식범위를 확장시키고 보다 안전하고 자연스런 자율주행을 지원할 수 있다. 이러한 자율협력주행 차량을 공공도로에서 운행하기 위해서는 V2X 보안통신의 신뢰성이 사전에 검증되어야 한다. 본 논문에서는 자율협력주행을 위한 V2X 보안통신에 대한 테스트 시나리오와 테스트 절차를 제안하고 검증 결과를 제시한다.

• 한국ITS학회 논문지
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• 제22권5호
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• pp.182-199
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• 2023

정부는 2021년부터 다부처 연구개발사업으로 자율주행기술개발혁신사업을 추진해오고 있다. 해당 연구개발사업에서 개발되는 자율주행차와 서비스 기술은 추후 선정된 리빙랩 도시를 대상으로 일반인들에게 제공한다는 계획이다. 특히 서비스분야는 해당 서비스별 목적과 특성에 따라 안전하고 안정적인 서비스가 가능한 공간적 범위와 운행구간을 선정하는 것이 중요하다. 본 연구에서는 향후 Level 4 수준의 자율주행서비스 제공 구역 설정 방법론을 개발하기 위한 기초 연구로서 기존 공개된 논문 및 관련 문헌조사를 통해 Level 4 수준의 자율주행서비스를 위한 정적인 ODD 구성요소를 재분류하고, 자율주행의 안전성에 미치는 공간적인 영향 요인에 대하여 Level 3 자율주행차 실제 주행데이터 및 공간정보분석 기법을 활용하여 분석하였다. 공간정보분석 기법을 통해 총 6개의 주행모드변경(제어권전환) 다발 지점이 도출되었고, 해당 지점의 중복된 정적인 ODD 구성요소 확인 결과 자율주행의 안전성에 영향을 미치는 요인은 횡단보도, 신호등, 교차로, 자전거 도로, 포켓차로, 주의 표지판, 중앙분리대로 나타났다. 이러한 공간정보분석을 통한 자율주행의 공간적 요인분석은 자율주행기술개발혁신사업의 리빙랩 도시뿐만 아니라 현재 확대·운영되고 있는 자율주행차 시범운행지구에서 자율주행서비스 운영지구 선정에도 기초연구로 활용될 것으로 기대한다.

• 자동차안전학회지
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• 제11권4호
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• pp.50-56
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• 2019

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which use a variety of sensor systems - ultrasonics, cameras, lidars and radars - and communication systems. It is necessary to examine the electromagnetic immunity of vehicles equipped with those systems. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside. It is difficult to create test environments in which the radar sensor systems of vehicles work properly in the test chamber. In this study, test jigs were designed and tested and as a result they are shown to be effective to create test environments for electromagnetic immunity tests of vehicles equipped with radar sensors. We also proposed additional safety standards for immunity tests of vehicles with radar systems that currently do not exist.

• 자동차안전학회지
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• 제12권4호
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• pp.7-12
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• 2020

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which use a variety of sensor systems - ultrasonics, cameras, lidars and radars - and communication systems. It is necessary to examine the electromagnetic immunity of vehicles equipped with the sensor systems due to the fact that the normal operation of those systems is very important to the safety of the vehicles. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside. It is difficult to create test environments in which the camera sensor systems of vehicles work properly in the test chamber. In this study, test jigs were designed and tested and as a result they are shown to be effective to create test environments for electromagnetic immunity tests of vehicles equipped with camera sensors. We also proposed additional safety standards for immunity tests of vehicles with camera systems that currently do not exist.

• 자동차안전학회지
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• 제15권4호
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• 자동차안전학회지
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• 제14권2호
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.