• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.12
• /
• pp.4697-4706
• /
• 2010

This paper suggested the optimal operating design method using simulation and ANP(Analytic Network Process) for mass-customization in the automotive component manufacturing industry. For this, first of all, we built the simulation model including various and complex factors in the field, and estimated the meta-model by RSM(Response Surface Method). Secondly using ANP, we calculated the weight of relative importance of evaluation factors gathered from decision makers. And then, we proposed the optimal operation designs by MOGA(Multi-Objective Genetic Algorithm), analyzed results of them. Moreover, by comparing the results with the consequences using AHP(Analytic Hierarchy Process), we showed its superiority of suggested method to the manner using AHP, because it reflects inner, outer dependency, and inter-relation among judgement factors. In conclusion, through this process, we can present the better way to serve mover effective, precise, and accurate information to decision makers when they build operation design for mass-customization system as automotive parts production system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.1
• /
• pp.6-11
• /
• 2011

This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.

• Annual Conference of KIPS
• /
• 2022.05a
• /
• pp.531-534
• /
• 2022

승차 공유, 카풀, 렌터카의 이용률이 증가하면서 많은 사용자가 동일한 차량에 로컬 액세스 할 수 있는 시나리오가 더욱 보편화됨에 따라 차량 네트워크에 대한 공격 가능성이 커지고 있다. 차량용 CAN Bus Network에 대한 DoS(Denial of Service), Fuzzy Attack 및 Replay Attack과 같은 공격은 일부 ECU(Electronic Controller Unit) 비활성 및 작동 불능 상태를 유발한다. 에어백, 제동 시스템과 같은 필수 시스템이 작동 불가 상태가 되어 운전자에게 치명적인 결과를 초래할 수 있다. 차량 네트워크 침입 탐지를 위하여 많은 연구가 진행되고 있으나, 기존 화이트리스트를 이용한 탐지 방법은 새로운 유형의 공격이 발생하거나 희소성이 높은 공격일 때 탐지하기 어렵다. 본 논문에서는 인공신경망 기반의 CAN 버스 네트워크 침입 탐지 기법을 제안한다. 제안하는 침입 탐지 기법은 2단계로 나누어 진다. 1단계에서 정상 패킷 분포를 학습한 VAE 모형이 이상 탐지를 수행한다. 이상 패킷으로 판정될 경우, 2단계에서 인코더로부터 추출된 잠재변수와 VAE의 재구성 오차를 이용하여 공격 유형을 분류한다. 분류 결과의 신뢰점수(Confidence score)가 임계치보다 낮을 경우 학습하지 않은 공격으로 판단한다. 본 연구 결과물은 정보보호 연구·개발 데이터 첼린지 2019 대회의 차량 이상징후 탐지 트랙에서 제공하는 정상 및 3종의 차량 공격시도 패킷 데이터를 대상으로 성능을 평가하였다. 실험을 통해 자동차 제조사의 규칙이나 정책을 사전에 정의하지 않더라도 낮은 오탐율로 비정상 패킷을 탐지해 낼 수 있음을 확인할 수 있다.

• Journal of Platform Technology
• /
• v.11 no.6
• /
• pp.13-20
• /
• 2023

Regularly inspecting vehicle tires' condition is imperative for driving safety and comfort. Poorly maintained tires can pose fatal risks, leading to accidents. Unfortunately, manual tire visual inspections are often considered no less laborious than employing an automatic tire inspection system. Nevertheless, an automated tire inspection method can significantly enhance driver compliance and awareness, encouraging routine checks. Therefore, there is an urgency for automated tire inspection solutions. Here, we focus on developing a deep learning (DL) model to predict cracked tires. The main idea of this study is to demonstrate the comparative analysis of DenseNet121, VGG-19 and EfficientNet Convolution Neural Network-based (CNN) Transfer Learning (TL) and suggest which model is more recommended for cracked tire classification tasks. To measure the model's effectiveness, we experimented using a publicly accessible dataset of 1028 images categorized into two classes. Our experimental results obtain good performance in terms of accuracy, with 0.9515. This shows that the model is reliable even though it works on a dataset of tire images which are characterized by homogeneous color intensity.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.3
• /
• pp.66-77
• /
• 2014

UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.3
• /
• pp.283-290
• /
• 2016

Even though existing methods for orthophoto production in traditional photogrammetry are effective in large areas, they are inefficient when dealing with change detection of geometric features and image production for short time periods in small areas. In recent years, the UAV (Unmanned Aerial Vehicle), equipped with various sensors, is rapidly developing and has been implemented in various ways throughout the geospatial information field. The data and imagery of specific areas can be quickly acquired by UAVs at low costs and with frequent updates. Furthermore, the redundancy of geospatial information data can be minimized in the UAV-based orthophoto generation. In this paper, the orthophoto and DEM (Digital Elevation Model) are generated using a standard low-end UAV in small sloped areas which have a rather low accuracy compared to flat areas. The RMSE of the check points is σ_H = ±0.12 m on a horizontal plane and σ_V = ±0.09 m on a vertical plane. As a result, the maximum and mean RMSE are in accordance with the working rule agreement for the airborne laser scanning surveying of the NGII (National Geographic Information Institute) on a 1/500 scale digital map. Through this study, we verify the possibilities of the orthophoto generation in small slope areas using general-purpose low specification UAV rather than a high cost surveying UAV.

• Journal of Korean Society of Transportation
• /
• v.19 no.4
• /
• pp.35-47
• /
• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Journal of Korean Society of Transportation
• /
• v.26 no.3
• /
• pp.41-51
• /
• 2008

As the local bus service diagram after the bus route reform is studied by variable analysis based on traffic card data and income adjustment data, the characteristic of the local bus system is revealed in Busan Metropolitan city. The relationship between traveling length and traveling time is influenced by traveling velocity. In order to keep a headway within 10 minutes, bus service number per minute should be over 0.1013 vehicles. The traveling time of afternoon is generally longer than that of forenoon. Compared with the bus used by a lot people, the deviation of that used by a few people is larger in the all cases of length, headway, time and velocity. According to the analysis of the relationship among card trip number, average income and transfer rate, the relationship between card trip number and average income is expressed as linear function in the general bus and as exponential function in the high-grade & rapid bus. The 1% increase of transfer rate is equal to 6.3 trip/vehicle/day decrease and 4.9 trip/vehicle/day decrease in two bus types respectively. The four effective variables are defined by the discriminant analysis between the profitable routes and the unprofitable; According to discriminant size, bus service number per km, bus via suburb, subway meeting number, bus via university. In order to increase the income when the minibus will be included among public transit transfer system in 2008, it should be necessary to settle the bus network and revitalize the public transit better. In order to decrease the cost, it should be necessary to reorganize the hierarchy between the local bus and the minibus better.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.5D
• /
• pp.727-737
• /
• 2011

The emergency restoration scenarios for efficient railway accident management and restoration were developed. The emergency restoration procedures defined by the worst case of emergency restoration and the important events was proposed based on questionnaires from specialists and the result of survey. Via these studies, the railway accident in the tunnel could be the worst case among all railway accident types. Therefore, educations for a restoration team in confined area condition should be planned and performed to recover the worst case accident. In order for the emergency restoration, when a railway accident is occurred, the restoration should be performed in orders of handing collapse of facilities, burying track, and derailment of vehicle in tunnel based on the statistical analysis. The result of priorities were established by the period of restoration. The standard operation system for efficient railway accident management was developed by synthesizing the worst case for rapid emergency restoration, and important events for the standard operation procedures according to each emergency restoration type. Through this study, the restoration operation system of railway accident are recommended. This paper suggests to develop emergency restoration scenarios for the efficient railway accident management and recovery system. The study results will contribute not only for insuring punctuality, but also for minimizing delays from accidents. Therefore, emergency restoration scenarios will play a major role in the SOP for the damage limitation and the prevention of accident spread.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_1
• /
• pp.987-997
• /
• 2019

Recently the demand for drones is rapidly increasing, as developing Unmanned Aerial Vehicle (UAV) and growing interest in them. Compared to traditional satellite and aerial imagery, it can be used for various researches (environment, geographic information, ocean observation, and remote sensing) because it can be managed with low operating costs and effective data acquisition. However, there is a disadvantage in that only a small area is acquired compared to the satellite and an aircraft, which is a traditional remote sensing method, depending on the battery capacity of the UAV, and the distance limit between Ground Control System (GCS) and UAV. If remote control at long range is possible, the possibility of using UAV in the field of remote sensing can be increased. Therefore, there is a need for a communication network system capable of controlling regardless of the distance between the UAV and the GCS. The distance between UAV and GCS can be transmitted and received using simple radio devices (RF 2.4 GHz, 915 MHz, 433 MHz), which is limited to around 2 km. If the UAV can be managed simultaneously by improving the operating environment of the UAV using a Long-Term Evolution (LTE) communication network, it can make greater effects by converging with the existing industries. In this study, we performed the maximum straight-line distance 6.1 km, the test area 2.2 ㎢, and the total flight distance 41.75 km based on GCS through LTE communication. In addition, we analyzed the possibility of disconnected communication through the base station of LTE communication.