PURPOSES : This study is conducted to evaluate the development of materials for extinguishing ESS(Energy Storage System) fires in electric vehicles using industrial byproducts. METHODS : Grout containing an appropriate amount of fly ash, silica fume, blast furnace slag powder, and ferronikel slag, which are industrial byproducts, was prepared. The fluidity, stress, and mechanical properties were evaluated in accordance with standard test methods. RESULTS : The fluidity of the materials used for the evolution of ESS fires differed depending on the material of the industrial byproducts. In the case of blast furnace slag, its fluidity is low owing to viscosity even when it content is high, and the use of ferronikelsrag is shown to be suitable for the evolution of ESS fires in fluidity and curing tests. CONCLUSIONS : Fire-extinguishing materials using industrial byproducts require a long curing time but exhibit the fluidity required for ESS fire extinguishment. In particular, the curing and fluidity of Peronikel slag and fly ash are suitable for ESS fire extinguishing.

In order to determine the future direction of Busan City’s tree planting policy in accordance with changes in automobile fuel and air pollutants, this study selected representative tree species planted in Busan and identified the biogenic volatile organic compounds (BVOCs) emission rate and characteristics of each species. First, representative tree species were selected for each street tree species, forest tree species, and park tree species, and the emission rate and major components of BVOCs were investigated for each tree species. Furthermore, by comparing the ozone generation potential (POCP) for each tree species, tree species with a low emission rate were selected. According to the POCP comparison, P. yedoensis, G. biloba, Z. serrata and C. retusus were selected as roadside tree species, P. densiflora and C. obtusa as forest species, and A. palmatum, C. japonica, and Q. myrsinaefolia were deemed suitable for park species. However, in the case of P. occidentalis, Quercus, and M. glyptostroboides, the emission rates of BVOCs were found to be high. Despite this, these tree species were found to display excellent CO2 absorption and carbon storage. The concentration of NOx in the city center is likely to decrease due to the current trend of transitioning to eco-friendly cars worldwide, resulting in less cars that rely on fossil fuels. Therefore, in the current climate where NOx emissions are still high, planting tree species with a low BVOCs emission rate would be an optimal approach. On the other hand, if the NOx concentration in the city is found to be very low due to changes in automobile fuel use, planting tree species with excellent BVOCs emission capacity and CO2 absorption would be ideal.

우리나라는 교통사고 사망자수 감축을 위해 다양한 교통안전 개선사업을 지속적으로 추진하고 있다. 특히, 보행자 안전 강화를 위한 보행환경개선사업은 중앙정부 및 지방정부를 중심으로 시설, 제도, 교육ž홍보 등 다양한 방법으로 수행되고 있다. 최근 횡단보도 보행자 안전 강화를 위한 시설 개선 사례로 활주로형 횡단보도가 설치ž운영되고 있다. 활주로형 횡단보도는 야간에 운전자 시인성을 증진하고 보행자의 안전성을 확보하는 시설물이다. 그러나 신규로 설치되는 활주로형 횡단보도의 정량적인 보행안전 개선 효과에 대한 연구는 부 족하다. 본 연구에서는 보행환경개선사업을 통해 읍․면지역에 신규 설치되는 활주로형 횡단보도의 효과를 시설물 접근로 진입 차량 평 균 주행 속도 조사를 통해 분석하였다. 총 8개 지점의 활주로형 횡단보도를 대상으로 접근로 진입 차량 평균 주행 속도를 조사하였으 며, 평균 속도 감소율은 15.3%이고, 속도 최대 감소율은 27.4%로 나타나는 것으로 분석되었다. 이와 같이 무단횡단이 빈번이 관측되는 읍․면지역의 경우 활주로형 횡단보도의 설치함으로써 접근하는 차량의 속도를 저감시키는 것으로 확인하였다. 향후 보행자 교통사고 저감이 필요한 읍․면지역에 설치 시 긍정적인 효과를 기대할 수 있을 것으로 사료된다

In South Korea, the level of Highway Pavement Management System (HPMS) was developed since early 2000. During this time numbers of professional pavement condition monitoring equipment were developed and applied in the actual field. One of the remarkable results is 3D Pavement condition Monitoring profiler vehicle (3DPM) designed and developed in Korea Expressway Corporation Research Division (KECRD). Thanks to this equipment, The surface condition of current pavement can successfully be monitored and proper following management strategy cab be established. However, the inner condition of pavement layer cannot be monitored dur to limitation of 3DPM equipment. In this paper, Bending Beam Rheometer (BBR) mixture creep test was performed to verify the effectiveness of current 3DPM equipment. It was found that the current 3DPM equipment has reasonable feasibility on surveying pavement condition.

Evaluation of low temperature performance of asphalt mixture is significant not only for mitigating transverse thermal cracking but also for preventing potential traffic accidents. In addition, the engineers in pavement agency need to inform the proper pavement section where urgent management is needed. Since early 2000, Korea Expressway Corporation Research Division (KECRD) developed an 3D Pavement condition Monitoring profiler vehicle (3DPM) to survey expressway pavement surface condition precisely. The management of whole expressway network became more precise, effective and efficient than before due to application of 3DPM and HPMS. One thing recommended is: performing extensive mechanical test and corresponding data analysis work procedure to further strengthen the feasibility of current 3DPM approach and HPMS. In this paper two activities were considered: first, the pavement section where the urgent care is recommended is selected by means of 3DPM approach. Then asphalt mixture cores were acquired on that specified section then low temperature fracture test: Semi Circular Bending (SCB) test, was performed. The mechanical parameters, energy release rate and fracture toughness were computed then compared. It is concluded that the current 3DPM approach in KEC can successfully evaluate and analyze selected pavement condition. However, more extensive experimental works are needed to further strengthen the current pavement analyzing approaches.

PURPOSES : This study develops a model that can estimate travel speed of each movement flow using deep-learning-based probe vehicles at urban intersections. METHODS : Current technologies cannot determine average travel speeds for all vehicles passing through a specific real-world area under obseravation. A virtual simulation environment was established to collect information on all vehicles. A model estimate turning speeds was developed by deep learning using probe vehicles sampled during information processing time. The speed estimation model was divided into straight and left-turn models, developed as fully-offset, non-offset, and integrated models. RESULTS : For fully-offset models, speed estimation for both straight and left-turn models achieved MAPE within 10%. For non-offset models, straight models using data drawn from four or more probe vehicles achieved a MAPE of less than 15%. The MAPE for left turns was approximately 20%. CONCLUSIONS : Using probe-vehicle data(PVD), a deep learning model was developed to estimate speeds each movement flow. This, confirmed the viability of real-time signal control information processing using a small number of probe vehicles.

The electrification of transportation is expected to greatly contribute to achieving the global climate change target. This study analyzed technological competitiveness in the fuel cell electric vehicle (FCEV) field based on patent family and citation index. Technology analysis was conducted by dividing FECV into six sub-technology areas based on IPC with fuel cell system, fuel cell technology, vehicle system, hydrogen storage and fueling, catalyst technology and etc. The largest number of patents are being filed in the fuel cell system technology field, and the fields with high growth rates over the past 10 years (2012-2022) were vehicle systems (12.4%) and hydrogen storage fuel field(11.5%). As of 2021, among global automakers, Toyota ranks the first in patent applications for FECV followed by Hyundai Motors in Korea, followed by Honda and Audi, with an average annual growth rate of 19.8%, the highest among competitors.

본 연구에서는 운전 시뮬레이션을 사용하여 자율주행 환경을 구현한 후 3-수준 자율주행 조건에서 자율주행 차량 (automated vehicle: AV)으로부터 운전자에게 전달되는 제어권 인수 요구(takeover request: TOR) 정보의 양상(시각, 청각 및 시각+청각) 및 도로 형태(직선도로와 곡선도로)에 따라 운전자의 제어권 인수 시간(takeover time: TOT) 및 정신적 작업부하(제어권 인수 이후에 운전자들이 경험한 주관적 작업부하와 심장박동수에서의 변화)가 어떻게 차별 화되는지 분석하였다. 본 연구의 결과를 요약하면 다음과 같다. 먼저, AV로부터 TOR이 제시된 이후 실험참가자들 이 보인 TOT에 대한 분석 결과, TOR 정보양상의 측면에서는 시각 정보가 가장 빠른 TOT를 이끌어 낸 반면 청각 정보 조건에서 가장 느렸고, 도로 형태 측면에서는 직선도로 조건에 비해 곡선도로 조건에서의 TOT가 유의하게 더 느렸으며, 특히 청각 정보 조건에서 도로 형태에 따른 TOT에서의 차이가 가장 컸다. 둘째, 정신적 작업부하에 대한 분석 결과, TOR 정보가 시각 혹은 시각+청각적으로 제시된 조건에 비해 청각적으로 제시된 조건에서 주관적 작업부 하 측정치와 심장박동수 변화 크기 모두 전반적으로 더 낮았고 특히, 심장박동수 변화의 경우 이러한 경향은 곡선도 로 조건에서만 관찰되었다. 이러한 결과는 TOR 정보의 양상과 도로 형태에 따라 운전자의 TOT와 정신적 작업부하 수준이 달라질 수 있고, 특히 TOT가 빠를수록 정신적 작업부하 수준은 상대적으로 더 높아질 수 있음을 시사한다.

PURPOSES : Demonstrated performance degradation of LiDAR for vehicle and pedestrian dummy in rainy and foggy road conditions. METHODS : In real-scale rain and fog road conditions, adjust the distance between LiDAR and the measurement target from 10m to 70m (in 10m interval), measure LiDAR NPC (number of point cloud) and intensity, and compare the resulting numerical values. RESULTS : LiDAR's NPC and Intensity showed statistically significant differences by overall weather condition (normal, rain, fog), and the values were found to be larger in the order of normal>rainfall>fog. In the case of vehicles, sunder rain conditions, NPC and intensity are recognized even at 70m as in normal conditions, but under fog conditions, NPC and intensity are measured only up to 30m. In the case of pedestrians, the reflective area size is smaller than that of vehicles, so they are recognized only up to 30m in rainy conditions, and NPC and intensity are measured only up to 20m in fog conditions. CONCLUSIONS : It was confirmed that LiDAR performance deteriorates in rain and fog compared to normal.

PURPOSES : This study aims to develop a congestion mitigation strategy at lane drop bottleneck with low Connected and Automated Vehicle (CAV) penetration. METHODS : The proposed strategy is designed to assign a role of a moving bottleneck to CAVs to reduce low-speed lane changes at bottleneck locations, which are the main cause of bottleneck capacity drop. Through this, it aims to induce proactive upstream lane changes for Human-Driven Vehicles (HDVs,). Therefore, this study includes the control algorithm for CAVs, and the evaluation of the strategy assumes penetration rates of 5% and 10% in a Microsimulation VISSIM environment. The assessment is conducted by comparing the capacity drop and total travel time. Additionally, a sensitivity test for the parameter of the CAV control algorithm, reduced speed, is performed to find the optimal parameter. RESULTS : In this study, three scenarios, a) Base, b) CAV with no control, and c) CAV with control, are designed to evaluate the effects of the CAV control strategy. Analysis of segment density and lane change distribution reveals that the control strategy effectively prevented vehicle congestion due to the bottleneck effect. Additionally, the analysis of capacity changes before and after the bottleneck and total travel time shows the effectiveness of the control strategy. The sensitivity test on CAV control speed emphasized the importance of selecting an appropriate speed for maintaining efficient traffic flow. Lastly, as the CAV penetration rate increased, the control strategy exhibited greater effectiveness in mitigating capacity drop. CONCLUSIONS : The proposed strategy is intended for use at low CAV penetration rates and is expected to provide assistance in mitigating congestion at bottlenecks during the early stages of CAV commercialization. Furthermore, since the role of CAV in the strategy can be performed by CVs or even HDVs, it can be applied not only immediately but also in the near future.

PURPOSES : This study aims to perform a quantitative analysis of Forward Collision Warning and crash frequency using heavy vehicle driving data collected in expressway driving environments, and to classify the driving environments where Forward Collision Warnings of heavy vehicles occur for accident-prone areas and analyze their occurrence characteristics. METHODS : A bivariate Gaussian mixture model based on inter-vehicle distance gap and speed-acceleration parameters is used to classify the environment in which Forward Collision Warning occurs for heavy vehicles driving on expressways. For this analysis, Probe Vehicle Data of 80 large trucks collected by C-ITS devices of Korea Expressway Corporation from May to June 2022. Combined with accident information from the past five years, a detailed analysis of the classified driving environments is conducted. RESULTS : The results of the clustering analysis categorizes Forward Collision Warning environments into three groups: Group I (highdensity, high-speed), Group II (high-density, low-speed), and Group III (low-density, high-speed). It reveals a positive correlation between Forward Collision Warning frequency and accident rates at these points, with Group I prevailing. Road characteristics at sites with different accident incidences showed that on-ramps and toll gates had high occurrences of both accidents and warnings. Furthermore, acceleration deviation at high-accident sites was significant across all groups, with variable speed deviations noted for each warning group. CONCLUSIONS : The Forward Collision Warning of heavy vehicles on expressways is classified into three types depending on the driving environment, and the results of these environmental classifications can be used as a basis for building a road environment that reduces the risk of crashes for heavy vehicles.

PURPOSES : This study evaluates the effectiveness of traffic flow optimization when giving safety strategy guidance to a connected autonomous vehicle (CAV) based on information received through infrastructure cooperation in a V2X environment for non-signal intersection. METHODS : To evaluate the effectiveness of safety strategy guidance based on developed traffic flow control algorithm at a non-signalized intersection, it was implemented on simulation. A scenario based on the Level of Service (LOS) and the market penetration rate(MPR) of autonomous vehicles was established. The simulation results were divided into safety, operation, and environment to evaluate the effect, and the effect of optimizing traffic flow was finally derived through the integrated evaluation score. RESULTS : As a result, when safety strategy guidance was provided, the number of conflicts and CO emissions decreased by about 29% and about 15%, improving safety and environmental performance. In the case of operation, the mean of delay time was increased overall by 1%, but in the case of MPR 50 and above, the delay time was reduced by about 38%, thereby increasing operation. Finally, the aspect of traffic flow optimization, effectiveness of safety strategy guidance was derived through the integrated evaluation score, and the average integrated evaluation score improved from MPR 20 or higher. CONCLUSIONS : Providing guidance had the effect of optimizing traffic flow at a non-signal intersection. In the future, V2X communications will provide CAV with algorithm-based guidance developed in this study to control driving behavior. it will support safe and efficient driving at non-signal intersections.

PURPOSES : This study aims to understand the characteristics of accidents involving autonomous vehicles and derive the causes of accidents from road spatial information through autonomous vehicle accident reports. METHODS : For this study, autonomous vehicle accident reports collected and managed by the CA DMV were used as data sources. In addition, spatial characteristics and geometric data for accident locations were extracted by Google maps. Based on the collected data, the study conducted general statistics, text embedding, and cross-analysis to understand the overall characteristics of autonomous vehicle accidents and their relationship with road spatial features. RESULTS : The analysis results for characteristics of autonomous vehicle accidents, applying statistical analysis and text embedding techniques, reveal that the damages caused by autonomous vehicle accidents are often minor, and approximately half of the accidents are triggered by other vehicles. It is noteworthy that accidents where autonomous vehicles are at fault are not uncommon, and when the cause of the accident is within the autonomous vehicle, the accident risk can increase. The accident analysis results using spatial data showed that the severity of accidents increases when on-street parking is present, when dedicated lanes for bicycles and buses exist, and when bus stops are present. CONCLUSIONS : Through this study, geometric and spatial elements that appear to have an impact on autonomous driving systems have been identified. The findings of this study are expected to serve as foundational data for improving the safety of autonomous vehicle operations in the future.

ZnO/Cu/ZnO (ZCZ) thin films were deposited at room temperature on a glass substrate using direct current (DC) and radio frequency (RF, 13.56 MHz) magnetron sputtering and then the effect of post-deposition electron irradiation on the structural, optical, electrical and transparent heater properties of the films were considered. ZCZ films that were electron beam irradiated at 500 eV showed an increase in the grain sizes of their ZnO(102) and (201) planes to 15.17 nm and 11.51 nm, respectively, from grain sizes of 13.50 nm and 10.60 nm observed in the as deposited films. In addition, the film’s optical and electrical properties also depended on the electron irradiation energies. The highest opto-electrical performance was observed in films electron irradiated at 500 eV. In a heat radiation test, when a bias voltage of 18 V was applied to the film that had been electron irradiated at 500 eV, its steady state temperature was about 90.5 °C. In a repetition test, it reached the steady state temperature within 60 s at all bias voltages.

전기자동차의 빠른 확산은 지구온난화와 자연재해 대응을 위해 국제적으로 중요한 과제이다. 대중화를 위해 “캐즘(Chasm) 극복”은 필수적이나, 선행연구들은 전기차 초기시장 분석이 대부분이며 캐즘 단계의 연구는 다소 제한적이다. 본 연구는 전기차 초기 단계를 벗어나는 국내시장에서 소비자의 전기차 구매 주요 저해 요인과, 이에 영향을 주는 소비자의 인구통계학적 특성 및 자동차 관련 경험을 설문과 통계 기법을 통해 심층 분석하였다. 연구 결과, 한국 전기차 시장은 캐즘 전 단계로 판단되며, 전기차의 “기술에 대한 낮은 신뢰성”, “경제성에 대한 의문”, “충전-운전 불편성”이 전기차의 주요 수용 저해 요인으로 확인되었다. 지역에 따른 고속/완속 충전 인프라의 적절한 구축, 교육과 홍보를 통한 전기차의 인식개선, 전기차 수용에 우호적인 얼리어답터(Early adopter)의 전기차 수용 촉진은 캐즘을 극복하는 과정에서 중요한 역할을 할 것으로 판단된다.

In this study, the abnormal noise phenomenon generated intermittently in the shock absorber of the combat armored vehicle was approached from the side of the squeak joint to solve the phenomenon. In order to identify the cause of the noise, the factors causing friction in the shock absorber were checked from the viewpoint of problem product analysis, process, and design. As an improvement plan, by improving the non-lubricated section in the nitrogen chamber, the operating noise was reduced to a level lower than that of a general automobile engine along with the elimination of noise. Considering that this is a combat vehicle, it is judged that it has been improved so as not to affect the survivability and health of the crew during equipment operation. Through the improvement of this study, it is expected to prevent power loss and improve the emotional quality of our soldier.

Recently, in the case of the root industry, although it is a basic industry that forms the basis of manufacturing competitiveness, there continues to be a shortage of manpower due to reasons such as dangerous working environments, industrial economic difficulties, and low wage systems. In addition, the demand for automation of production lines using robots is increasing due to a shrinking labor market due to a decrease in the working population due to aging, higher wages, shorter working hours, and limitations of foreign workers. In this study, a system was developed to automate the injection molding process for producing ball valves for automobiles by applying robot system. The applied process flow consists of alignment and insertion of insert parts, and removal, transfer, and loading of the product after injection molding, which is currently performed manually. Through the application of the developed robot automation system, the cycle time was improved by more than 30% and the defect rate was reduced by more than 70%.