• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.53-60
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• 2014

Redundant handovers cause degraded quality of service to passengers in vehicle. This paper proposes a handover scheme suitable for users traveling in vehicles, which enables continuous learning of the handover process using a discrete-time Markov chain (DTMC). Through AdaBoost machine learning algorithm, the proposed handover scheme avoids unnecessary handover trials when a short dwell time in a target cell is expected or when the target cell is an intermediate cell through which the vehicle quickly passes. Simulation results show that the proposed scheme reduces the number of handover occurrences and maintains adequate throughput.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.225-236
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• 2011

Various applications of LBS (Location Based Services) are being developed to provide the customized service depending on user's location with progress of wireless communication technology and miniaturization of personalized device. To effectively process an amount of vehicles' location data, LBS requires the techniques such as vehicle observation, data communication, data insertion and search, and user query processing. In this paper, we propose the historical location index, GIP-FB (Group Insertion tree with Flexible Buffer Node) and the flexible buffer node technique to adjust the cost of data insertion and search. the designed GIP+ based index employs the buffer node and the projection storage to cut the cost of insertion and search. Besides, it adjusts the cost of insertion and search by changing the number of line segments of the buffer node with user defined time interval. In the experiment, the buffer node size influences the performance of GIP-FB by changing the number of non-leaf node of the index. the proposed flexible buffer node is used to adjust the performance of the historical location index depending on the applications of LBS.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.106-112
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• 2022

The purpose of this study is to explore ways of improving the motor vehicles safety certification system in preparation for the deployment of Lv.4 or higher autonomous vehicles. In order to effectively achieve the objectives of this study, theoretical and empirical research methodologies were employed, including literature review of prior research, government-published data, etc.; comparative research on legislative cases of other countries regarding motor vehicles safety certification; historical and legal research on domestic systems; legal analysis to explore approaches for improvement, etc. Some argue that the type approval system is needed in preparation for deploying autonomous vehicles, but there are several limitations in moving to the type approval system from the self-certification system currently adopted in Korea. First, there is a possibility that the system may be in conflict with the Korea-U.S. MOU regarding Foreign Motor Vehicles (1988) and the Korea-U.S. FTA (2011); second, there is a risk of undermining the cause of the self-certification system, which is the autonomy of manufacturers; third, the boundary between autonomous vehicles and non-autonomous vehicles is unclear; and fourth, the type approval system may hinder technological competitiveness. On the other hand, considering that the Korea-U.S. FTA and the UNECE IWVTA recognize exceptions to deal with road safety and risks to human health or the environment, and have a pre-certification system for some auto parts such as pressure-resistant containers, it can be said that there is room to introduce the type approval system for supplementation purposes. To improve the motor vehicles safety certification system while ensuring the safety of autonomous vehicles of Lv.4 or higher, the targets of type approval should be defined and the criteria, procedures, etc. for type approval should be established. At the same time, the consistency between motor vehicle-related laws and harmonization with international standards need to be considered.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.354-372
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• 2016

This study identified factors affecting the crash severity at freeway work zones. A nice feature of this study was to take into account the characteristics of work zone traffic management in analyzing traffic safety concerns. In addition to crash records, vehicle detection systems (VDS) data and work zone historical data were used for establishing a dataset to be used for statistical analyses based on an ordered probit model. A total of six safety improvement strategies for freeway work zones, including traffic merging method, guidance information provision, speed management, warning information systems, traffic safety facility, and monitoring of effectiveness for countermeasures, were also proposed.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.111-124
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• 2021

Recently, Interest in the restoration and 3D reconstruction of cultural properties due to the fire of Notre Dame Cathedral on April 15, 2019 has been focused once again after the 2008 Sungnyemun fire incident in South Korea. In particular, research to restore and reconstruct the actual measurement of cultural properties using LiDAR(Light Detection and ranging) and conventional surveying, which were previously used, using various 3D reconstruction technologies, is being actively conducted. This study acquires data using unmanned aerial imagery of UAV(Unmanned Aerial Vehicle), which has recently established itself as a core technology in the era of the 4th industrial revolution, and the existing CRP(Closed Range Photogrammetry) and terrestrial LiDAR scanning for the Recumbent Buddha of Unju Temple. Then, the 3D reconstruction was performed with three fusion models based on SfM(Structure-from-Motion), and the reproducibility and accuracy of the models were compared and analyzed. In addition, using the best fusion model among the three models, the relationship with the Polar Star(Polaris) was confirmed based on the real world coordinates of the Recumbent Buddha, which contains the astronomical history of Buddhism in the early 11th century Goryeo Dynasty. Through this study, not only the simple external 3D reconstruction of cultural properties, but also the method of reconstructing the historical evidence according to the type and shape of the cultural properties was sought by confirming the historical evidence of the cultural properties in terms of spatial information.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.803-811
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• 2014

The moment when Electrical Vehicle (EV) starts charging or discharging is one of the most important parameters in estimating the impact of EV load on the grid. In this paper, a decision-making problem of determining the start time of charging and discharging during allowed period is proposed and studied under the uncertainty of real-time price. Prospect theory is utilized in the decision-making problem of this paper for it describes a kind of decision making behaviors under uncertainty. The case study uses the parameters of Springo SGM7001EV and adopts the historical realtime locational marginal pricing (LMP) data of PJM market for scenario reduction. Prospect values are calculated for every possible start time in the allowed charging or discharging period. By comparing the calculated prospect values, the optimal decisions are obtained accordingly and the results are compared with those based on Expected Utility Theory. Results show that with different initial State-of-Charge ($SoC_0$) and different reference points, the optimal start time of charging can be the one between 12 a.m. to 3 a.m. and optimal discharging starts at 2 p.m. or 3p.m. Moreover, the decision results of Prospect Theory may differ from that of the Expected Utility Theory with the reference points changing.