• Yaw Moment Control Algorithm based on Estimated Vehicle Mass for Manual-Shift Commercial Vehicles

    질량 추정기 기반 수동 변속 상용차용 요 모멘트 제어 알고리즘

    Kim, Jayu, Cha, Hyunsoo, Park, Kwanwoo and Yi, Kyongsu

    김자유, 차현수, 박관우, 이경수

    This paper presents a yaw moment control based on estimated mass for manual-shift commercial vehicles. In yaw moment controller, parameter uncertantiy of … + READ MORE
    This paper presents a yaw moment control based on estimated mass for manual-shift commercial vehicles. In yaw moment controller, parameter uncertantiy of vehicle mass is important because the desired yaw moment depends on vehicle parameter. However, in the case of commercial vehicle, the weight of the loaded vehicle is more than twice as much as compared to the unloaded vehicle. The proposed algorithm estimates the vehicle mass by using the longitudinal dynamic and gear shifting characteristics. The estimated mass is used to adaptively modify the vehicle parameters. In addition, this paper estimates the chamber pressure of a pneumatic brake and generates the target yaw moment through on/off valve control. MATLAB/Simulink and Trucksim were performed under sine with dwell test. The results demonstrate that the proposed algorithm improves the lateral and rollover stability. - COLLAPSE
    30 June 2022
  • V2V based Cut-In Vehicle Yield Algorithm for Congested Traffic Autonomous Driving

    혼잡 교통류에서의 V2V 기반 Cut-In 차량 양보 거동 계획 알고리즘

    Kim, Changhee, Chae, Heungseok, Yoon, Youngmin and Yi, Kyongsu

    김창희, 채흥석, 윤영민, 이경수

    This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to … + READ MORE
    This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles. - COLLAPSE
    30 June 2022
  • An Adaptive ROI Decision for Real-time Performance in an Autonomous Driving Perception Module

    자율주행 인지 모듈의 실시간 성능을 위한 적응형 관심 영역 판단

    Lee, Ayoung, Lee, Hojoon and Yi, Kyongsu

    이아영, 이호준, 이경수

    This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole … + READ MORE
    This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road’s design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs. - COLLAPSE
    30 June 2022
  • Development of Multiple RLS and Actuator Performance Index-based Adaptive Actuator Fault-Tolerant Control and Detection Algorithms for Longitudinal Autonomous Driving

    다중 순환 최소 자승 및 성능 지수 기반 종방향 자율주행을 위한 적응형 구동기 고장 허용 제어 및 탐지 알고리즘 개발

    Oh, Sechan, Lee, Jongmin, Oh, Kwangseok and Yi, Kyongsu

    오세찬, 이종민, 오광석, 이경수

    This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed … + READ MORE
    This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker). - COLLAPSE
    30 June 2022
  • LiDAR Static Obstacle Map based Position Correction Algorithm for Urban Autonomous Driving

    도심 자율주행을 위한 라이다 정지 장애물 지도 기반 위치 보정 알고리즘

    Noh, Hanseok, Lee, Hyunsung and Yi, Kyongsu

    노한석, 이현성, 이경수

    This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is … + READ MORE
    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. - COLLAPSE
    30 June 2022
  • Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data

    딥러닝 데이터 활용한 신호등 색 인식 알고리즘 개발

    Baek, Seoha, Kim, Jongho and Yi, Kyongsu

    백서하, 김종호, 이경수

    The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that … + READ MORE
    The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios. - COLLAPSE
    30 June 2022
  • LiDAR based Real-time Ground Segmentation Algorithm for Autonomous Driving

    자율주행을 위한 라이다 기반의 실시간 그라운드 세그멘테이션 알고리즘

    Lee, Ayoung and Yi, Kyongsu

    이아영, 이경수

    This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider … + READ MORE
    This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider Random Sample Consensus (Ransac) Algorithm to process lidar ground data. Ransac designates inlier and outlier to erase ground point cloud and classified PCD into two parts. Test results show removal of PCD from ground area by distinguishing inlier and outlier. The paper validates ground rejection algorithm in real time calculating the number of objects recognized by ground data compared to lidar raw data and ground segmented data based on the z-axis. Ground Segmentation is simulated by Robot Operating System (ROS) and an analysis of autonomous driving data is constructed by Matlab. The proposed algorithm can enhance performance of autonomous driving as misrecognizing circumstances are reduced. - COLLAPSE
    30 June 2022
  • A Study on the ACC Safety Evaluation Method Using Dual Cameras

    듀얼카메라를 활용한 ACC 안전성 평가 방법에 관한 연구

    Kim, Bong-Ju and Lee, Seon-Bong

    김봉주, 이선봉

    Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among … + READ MORE
    Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver’s driving fatigue through the control of the vehicle’s longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results. - COLLAPSE
    30 June 2022
  • Development of Target Vehicle State Estimation Algorithm Using V2V Communication

    V2V 통신을 이용한 상대 차량 상태 추정 알고리즘 개발

    Kwon, Woojin, Jo, Ara and Yi, Kyongsu

    권우진, 조아라, 이경수

    This paper describes the development of a target vehicle state estimation algorithm using vehicle-to-vehicle (V2V) communication. Perceiving the state of the target … + READ MORE
    This paper describes the development of a target vehicle state estimation algorithm using vehicle-to-vehicle (V2V) communication. Perceiving the state of the target vehicle has great importance for successful autonomous driving and has been studied using various sensors and methods for many years. V2V communication has advantage of not being constrained by surrounding circumstances relative to other sensors. In this paper, we adopt the V2V signal for estimating the target vehicle state. Since applying only the V2V signal is improper by its low frequency and latency, the signal is used as additional measured data to improve the estimation accuracy. We estimate the target vehicle state using Extended Kalman filter (EKF); a point mass model was utilized in process update to predict the state of next step. The process update is followed by measurement update when ego vehicle receives V2V information. The proposed study evaluated state estimation by comparing input V2V information in an experiment where the ego vehicle follows the target vehicle behind it. - COLLAPSE
    30 June 2022
  • Strategy for V2E Performance Assurance Technology Development Using the Kano Model

    Kano 모델을 활용한 V2E 성능확보기술 개발 전략

    Jang, Jeong Ah, Son, Sungho and Lee, Jung Ki

    장정아, 손성호, 이정기

    Automated vehicles (AVs) are coming to our roadways. In practice, there are still several challenges that can impede the AV sensors are … + READ MORE
    Automated vehicles (AVs) are coming to our roadways. In practice, there are still several challenges that can impede the AV sensors are polluted on various road conditions. In this paper, we propose a strategy for V2E performance assurance technology using Kano model. We are developing the vehicle sensor cleaning system about the three types of commonly used sensors: camera, radar, and LiDAR. Surveys were carried out in 30 AV’s experts on quality characteristics about V2E performance assurance technology. As a result, the Kano model developed to verify a major requirement of autonomous vehicle’s sensor cleaning system. It is expected that the Kano model will be actively used to verify the importance of V2E development strategy. - COLLAPSE
    30 June 2022
  • Analysis for Safety and Traffic Accident Case of ATV (All-Terrain Vehicle)

    사륜 오토바이의 안전 및 교통사고 사례 분석

    Choi, Youngsoo, Yoon, Yongmoon and Park, Jongchan

    최영수, 윤용문, 박종찬

    Recently, the use of ATV (All-Terrain Vehicle) has increased due to increase in leisure activities, and the awareness of safety and traffic … + READ MORE
    Recently, the use of ATV (All-Terrain Vehicle) has increased due to increase in leisure activities, and the awareness of safety and traffic accidents has improved, but it still insignificant compared to other transportation. Therefore, in this study, the current status and characteristics of traffic accidents related to ATVs were investigated, and actual ATV accident was analyzed. As a result, it was confirmed that the condition of the braking system directly connected to the safety of the ATV was not well maintained. For driver safety in the future, it is considered that it is necessary to strengthen safety regulations related to experience centers and rental companies handling AVTs and to conduct regular inspections in accordance with the Motor Vehicle Management Act. - COLLAPSE
    30 June 2022
  • A Study on the Development of Cu Free Friction Material of Composite Brake to Response Eco-friendly Regulation

    친환경 법규 대응을 위한 복합재 브레이크의 Cu Free 마찰재 개발에 관한 연구

    Shim, J. H., Lee, J. H., Shin, U. H., Lim, D. W. and Hyun, E. J.

    심재훈, 이중희, 신웅희, 임동원, 현은재

    Composite material is widely used in the automotive industries because it has excellent mechanical properties and is possible to reduce weight due … + READ MORE
    Composite material is widely used in the automotive industries because it has excellent mechanical properties and is possible to reduce weight due to the low density. However, there is a new obstacle to meet environment regulation like Cu less or Cu free regulation for the friction material. Although it is strongly demanded, there are few research results about that unfortunately. Unless this problem is not solved properly, it is impossible to apply composite brake system to vehicle. In this paper, a new eco-friendly friction material for composite brake system is represented to respond these regulations. To do this, friction characteristics between existing low steel friction material and new eco-friendly friction material are verified to secure performances for brake system such as effect characteristic, fade characteristic and wear characteristic. And composite brake gets the equivalent or better performance compared to a low steel friction material. Finally, this result contributes to the study of major principles for the development of eco-friendly friction material in the future. - COLLAPSE
    30 June 2022