상호안전성을 고려한 차대차 정면 충돌 안전성 선행 연구

이창민,신장호,김현우,박건호,박영준,Lee, Chang min,Shin, Jang ho,Kim, Hyun woo,Park, Kun ho,Park, Young joon 한국자동차안전학회 2017 자동차안전학회지 Vol.9 No.1

In recent years, NCAP regulations of many countries have induced automaker to improve the vehicle crashworthiness. But, the current NCAP regulations don't cover all types of traffic accidents. And rapid-increasing market share of compact cars and SUVs has brought for both consumer and automaker to pay more attention on crash compatibility. So, many countries have tried to develop the new crash test mode and update the present crash test mode. Especially, Euro NCAP has been developing a new impact protocol of the car-to-car frontal offset impact including the crash compatibility assessment. There are plans to introduce this new protocol in 2020, and it will be replaced the current Euro NCAP frontal offset impact. The test dummy in the front seats of this new test mode will be changed from 50% Hybrid-III male to 50% THOR male. This paper will address the vehicle responses, the occupant responses and the vehicle compatibility performance from a full vehicle crash test using the new car-to-car frontal offset test protocol of Euro NCAP.

이륜자동차의 전자파 적합성과 안전기준에 관한 연구

우현구,용부중 사단법인 한국자동차안전학회 2019 자동차안전학회지 Vol.11 No.1

Nowadays many two-wheeled motorcycles are used in leisure and express delivery industries. But studies of the electromagentic compatibility on motorcycles have seldom been performed and published. This paper has studied the electromagnetic safety of motorcycles considering international and domestic regulations and standards. Also, a series of experiments have been performed to evaluate the level of electromagnetic compatibility of commercially available motorcycles. As a result, detailed experimental procedures are proposed to secure the electromagnetic safety and can be used to confirm or revise the Korea Motor Vehicle Safety Standards.

수소연료전지자동차에 대한 안전기준 고찰

용기중,이광범,권해붕,Yong, Gee Joong,Lee, Kwang Bum,Kwon, Hae Boung 한국자동차안전학회 2014 자동차안전학회지 Vol.6 No.2

In the ongoing debates over the need to identify new sources of energy and to reduce the emissions of greenhouse gases. Hydrogen has emerged as one of the most promising alternatives due to its emissions from the vehicle being virtually zero. The governments have identified the development of regulations and standards as one of the key requirements for commercialization of hydrogen-fueled vehicles. Regulations and standards will helpful in overcoming technological barriers to commercialization. Developments of a technique for safety assessment of Hydrogen Fuel Cell Vehicle(HFCV) includes four tasks, research for regulation system and policy, hydrogen safety, vehicle operation safety and protection against high-voltage. The objective is to establish a technique for safety assessment and amend safety standards for HFCV and consequently reflect research results to vehicle management policy. We devised safety standards and evaluation techniques with regard to high-pressure gas and high voltage of hydrogen fuel cell vehicle. Korean Motor Vehicle Safety Standards(KMVSS) for HFCV was amended to June 10, 2014. including the results of the safety assessment technology for high-voltage and hydrogen characteristics.

Kano 모델을 활용한 V2E 성능확보기술 개발 전략

장정아,손성호,이정기 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.2

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.

사륜 오토바이의 안전 및 교통사고 사례 분석

최영수,윤용문,박종찬 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.2

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.

도심 자율주행을 위한 라이다 정지 장애물 지도 기반 위치 보정 알고리즘

노한석,이현성,이경수 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.2

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.

고속도로 주행 시 선행차량의 전방 긴급 장애물 회피에 따른 Car-to-Car Cut-out 시나리오 기반 AES 성능평가 방법 연구

김진석,이동훈 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.4

With the popularization of autonomous driving technology, safety has emerged as a more important criterion. However, there are no assessment protocol or methods for AES (Autonomous Emergency Steering). So, this study proposes AES assessment protocol and scenario corresponding to collision avoidance Car-to-Car scenario of Euro NCAP in order to prepare for obstacles that appear after the emergency steering of LV (Leading Vehicle) avoiding obstacles in front of. Autoware-based autonomous driving stack is developed to test and simulate scenario in CARLA. Using developed stack, it is confirmed that obstacle avoidance is successfully performed in CARLA, and the AES performance of VUT (Vehicle Under Test) is evaluated by applying the proposed assessment protocol and scenario.

카메라-라이다 센서 융합을 통한 VRU 분류 및 추적 알고리즘 개발

김유진,이호준,이경수,Kim, Yujin,Lee, Hojun,Yi, Kyongsu 한국자동차안전학회 2021 자동차안전학회지 Vol.13 No.4

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

저속 특장차의 도심 자율주행을 위한 신호등 인지 알고리즘 적용 및 검증

윤원섭,김종탁,이명규,김원균 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.4

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

듀얼카메라를 활용한 ACC 안전성 평가 방법에 관한 연구

김봉주,이선봉 사단법인 한국자동차안전학회 2022 자동차안전학회지 Vol.14 No.2

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.