Due to the complexity of urban area, the city vehicle routing problem has been a difficult problem. The problem has involved factors such as parking availability, road conditions, and traffic congestion, all of which increase transportation costs and delivery times. To resolve this problem, one effective solution can be the use of parcel lockers located near customer sites, where products are stored for customers to pick up. When a vehicle delivers products to a designated parcel locker, customers in the vicinity must pick up their products from that locker. Recently, identifying optimal locations for these parcel lockers has become an important research issue. This paper addresses the parcel locker location problem within the context of urban traffic congestion. By considering dynamic environmental factors, we propose a Markov decision process model to tackle the city vehicle routing problem. To ensure more real situations, we have used optimal paths for distances between two nodes. Numerical results demonstrate the viability of our model and solution strategy.

Military tanks and armored vehicles use tracks with excellent mobility in rough terrain, the transmission, a key component of tracked vehicle driving performance, performs shifting, steering and braking functions of tracked vehicles. There was concern about the deterioration of the driving performance of the tracked vehicle due to the occurrence of oil leakage in the output part of the transmission that rotates the track of the vehicle. Throughㅇ failure mechanism analysis and characteristic factor analysis using 4M(Man, Machine, Material, Method) quality management, it was confirmed that the factor affecting oil leakage in the output part was damage to the output shaft coupling surface, which is the contact surface of the output part oil seal. Based on this, a quality improvement plan was derived by applying a protective cap to prevent damage to the coupling surface, increasing the coupling surface hardness to improve the oil seal sealing function, and revising the work standard throughout production, process movement and assembly stages. The effectiveness of the proposed improvement was verified through a single transmission test, a power pack test, and a track vehicle installation test, and the effectiveness was verified through follow-up observation. It is expected that the improvements derived from this study will be utilized in the future analysis of similar equipment quality problems.

This study secured the field technology of z-axis auto-leveling according to the standalone lift boarding box structure, measured the weight measurement and usage time of the used load, and found the measured value of the deviation of the allowable range and rotation angle of the y-axis rotation range.The Z-axis leveling deviation of the boarding box can also be checked, and auto-leveling technology using a hydraulic system is a very useful technology, and it is judged that this technology can be applied to various forms using the acquired technology.

PURPOSES : This study explores the preference of shared autonomous vehicle service in an underground dedicated environment. METHODS : A stated preference survey was conducted to examine the mode choice behaviors on autonomous vehicle service competing with existing modes. Multinomial logit was employed to estimate the parameters of explanatory variables from the surveyed data. The model was estimated with alternative specific parameters rather than generic parameters. The value of time was also estimated using the parameters of the mode choice model. RESULTS : The results showed that the travel cost had the highest sensitivity to public transportation and the lowest to private cars. We also found that the value of the in-vehicle travel time was highest for private cars, lowest for public transportation, and intermediate for SAVs, suggesting that SAVs could serve as a premium public transport option. Additionally, the out-vehicle time coefficient was higher for public transportation compared to that for SAVs, indicating that users are more willing to tolerate longer out-vehicle times for SAVs due to their high-speed service compared to that of public transportation. CONCLUSIONS : This study presents a direction for policy regarding the adoption of shared autonomous vehicle services by considering the attributes that are valued by users of each mode.

PURPOSES : Even when autonomous vehicles are commercialized, a situation in which autonomous vehicles and regular drivers are mixed will persist for a considerable period of time until the percentage of autonomous vehicles on the road reaches 100%. To prepare for various situations that may occur in mixed traffic, this study aimed to understand the changes in traffic flow according to the percentage of autonomous vehicles in unsignalized intersections. METHODS : We collected road information and constructed a network using the VISSIM traffic simulation program. We then configured various scenarios according to the percentage of autonomous vehicles and traffic volume to understand the changes in the traffic flow in the mixed traffic by scenario. RESULTS : The results of the analysis showed that in all scenarios, the traffic flow on major roads changed negatively with the mix of autonomous vehicles; however, the increase or decrease was small. By contrast, the traffic flow on minor roads changed positively with a mix of autonomous vehicles. CONCLUSIONS : This study is significant because it proactively examines and designs traffic flow changes in congested traffic that may occur when autonomous vehicles are introduced.

PURPOSES : The purpose of this study is to identify the causes and expected problems of traffic flow in connection with ground roads that are expected to become stagnant owing to the increase in underground road infrastructure, and to derive methods to solve the problem in the future. METHODS : The basic design of underground roads is similar to that of tunnels. However, there is a point where the slope is large as the entering and exiting sections move underground. The ability of a heavy vehicle to assume a mound may vary depending on the slope. Therefore, in this study, a connection path section with a long slope was constructed using VISSIM, a simulation program, and it was verified whether analysis related to the slope and heavy vehicles in an underground road can be performed in the simulation. Subsequently, an analysis was conducted by setting a scenario and an effect index. In particular, this study analyzes internal delay patterns in the event of an unexpected situation on an underground connection road by performing shock wave analysis to analyze speed reduction according to heavy vehicles and slopes. RESULTS : A correlation between the slope of the underground road and decrease in the average speed according to the increasing rate of heavy vehicles was established. It was also possible to analyze the maximum length and duration of the delay connected to the rear in the event of a delay in the underground road and the shock wave speed transmitted to the rear. The analysis showed that the rate of increase in problems owing to delays ranged from 5% to 20% for the ratio of heavy vehicles. In particular, all effect scales increased significantly at a 9% slope. CONCLUSIONS : This study analyzes the causes of land congestion (slope and heavy vehicle mixing rate), which can be a major problem in underground roads in the future. In the future, by establishing lane-specific speed control strategies and lane control strategies based on this study, it will be necessary to derive solutions such as introducing traffic safety on the underground road by minimizing the shock wave delivered to the rear by providing information on traffic communication conditions inside the underground road to individual vehicles.

This study uses a frequency analyzer to measure and analyze the major alarm sounds of cars selected by domestic car manufacturer and car size, which are continuously improving in accordance with the continuous development of the automobile field. Therefore, the purpose is to find the alarm sound that modern people can hear best and find improvement measures accordingly. In the past, only the driving performance of vehicles was considered important, but as the industry and science developed, research was conducted to satisfy not only the driving performance of vehicles but also the comfort and emotional needs of drivers, such as ride comfort, safety, and noise issues. At the same time, it is progressing actively and continues to develop.

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.