• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.30-39
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• 2012

In this paper, a safe driving assistance system is proposed by detecting the status of driver's doze based on face and eye detection. By the level of the fatigue, safe driving system alarms or set the seatbelt on vibration. To reduce the effect of backward light and too strong solar light which cause a decrease of face and eye detection rate and false fatigue detection, post processing techniques like image equalization are used. Haar transform and PCA are used for face detection. By using the statistic of the face and eye structural ratio of normal Koreans, we can reduce the eye candidate area in the face, which results in reduction of the computational load. We also propose a new eye status detection algorithm based on Hough transform and eye width-height ratio, which are used to detect eye's blinking status which decides doze level by measuring the blinking period. The system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. In this paper, four algorithms are implemented and proposed algorithm is made based on the probability model and we achieves 84.88% of correct detection rate through indoor and in-car environment experiments. And also we achieves 69.81% of detection rate which is better result than that of other algorithms using IR camera.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.5
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• pp.23-29
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• 2015

In this study, human is the subject of driving a car, the actual EEG is a biological information in a number of reactions that are displayed while driving the vehicle by using a measuring device, occurs during travel of the road EEG to be collected, number of experiments the collected material on the basis of changes associated with running time, extracts the factors such as changes due to road geometry, and analysis was performed. The required changes in the EEG occurring during traveling experiment analysis alpha (${\alpha}$) waves, beta (${\beta}$) wave, after the primary extraction in the form of gamma (${\gamma}$) faction, the brain wave frequency of the entire period of the experiment change rate extracts, to calculate the change in frequency in response to EEG characteristics by applying the regression model to observe a learning effect in response to an increase in the number of experiments, as a result, depending on the number of experiments, EEG changes due to individual differences. The show, by repeatedly driving a section like this, it was possible to verify that comfortably travels driver accustomed in accordance with the stored road geometry and signal, safety facilities.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.11-17
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• 2016

In this paper, we proposed a multi-viewer system with multiple HD cameras based AVB(Audio Video Bridge) ethernet cable using IP networking, and FPGA(Xilinx Zynq 702) for bus safety systems. This AVB (IEEE802.1BA) system can be designed for the low latency based on FPGA, and transmit real-time with HD video and audio signals in a vehicle network. The proposed multi-viewer platform can multiplex H.264 video signals from 4 wide-angle HD cameras with existed ethernet 1Gbps. and 2-wire 100Mbps cables. The design of Zynq 702 based low latency to H.264 AVC CODEC was proposed for the minimization of time-delay in the HD video transmission of car area network, too. And the performance of PSNR(Peak Signal-to-noise-ratio) was analyzed with the reference model JM for encoding and decoding results in H.264 AVC CODEC. These PSNR values can be confirmed according the theoretical and HW result from the signal of H.264 AVC CODEC based on Zynq 702 the multi-viewer with multiple cameras. As a result, proposed AVB multi-viewer platform with multiple cameras can be used for the surveillance of audio and video around a bus for the safety due to the low latency of H.264 AVC CODEC design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.843-850
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• 2020

The purpose of this study is to evaluate the structural risk and weakness of a railway tank car through nonlinear collision analysis according to overseas collision safety standards. The goal is to propose a crash safety design guideline for railway tank cars for transporting dangerous goods in Korea. We analyzed the buffer impact test procedure of railway freight cars prescribed in EN 12663-2 and the tank puncture test criteria prescribed in 49CFR179. A nonlinear finite element model according to each standard was modeled using LS-DYNA, a commercial finite element analysis solver. As a result of the buffing impact test simulation, it was predicted that plastic deformation would not occur at a collision speed of 6 km/h or less. However, plastic deformation was detected at the rear of the center sill and at the tank center supporting the structure at a collision speed of 8 km/h or more. As a result of a head-on test simulation of tank puncture, the outer tank shell was destroyed at the corner of the tank head when 4% of the kinetic energy of the impacter was absorbed. The tank shell was destroyed in the area of contact with the impacter in the test mode analysis of tank shell puncture when the kinetic energy of the moving vehicle was reduced by 30%. Therefore, the simulation results of the puncture test show that fracture at the tank shell and leakage of the internal material is expected. Consequently, protection and structural design reinforcement are required on railway tank cars in Korea.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.

• Environmental and Resource Economics Review
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• v.29 no.3
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• pp.313-333
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• 2020

This paper shows that when the exchange rate changes, there are conflicting effects on improving the quality and increasing market share of eco-friendly vehicles. In a vertically differentiated duopoly model consisting of high quality clean cars and low quality internal combustion engine cars, I set up a two-stage noncooperative game under perfect information that the quality levels and the prices of the cars are competitively determined. The vehicles are assumed to be produced in countries that use distinct currencies. When the exchange rate of the country that produces low quality cars rises, the producer prefers to intensify competition due to the relatively lowed cost, and the incentive for quality improvement arises from the intension of attempting to reduce the degree of differentiation of quality level. At this time, the clean car manufacturing firm tries to avoid competition due to weakened competitiveness, and increases the quality level to expand quality differentiation. However, in this case, the market share of eco-friendly vehicles shrinks. On the other hand, if the exchange rate changes in the opposite direction, the market share of eco-friendly vehicles is expected to increase, but the quality of both cars are deteriorated, causing a conflict effect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.167-175
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• 2011

Evaluation of fuel consumption for the various road condition and vehicle type is necessary to perform the economic analysis of road construction which is important for the efficient design and management of road. Economic analysis of road should consider the social cost which can be divided into agency cost including initial construction expense, maintenance cost, and so on, and user cost consisting of vehicle operating cost, congestion cost, etc. Since vehicle operating cost depends on the traffic volume, fuel consumption that is a major part of vehicle operating cost will change by traffic volume as well. Fuel consumption is significantly affected by vehicle speed and road condition, especially the roughness. Thus, fuel consumption should be evaluated in terms of road condition, which is not currently considered. In this study, the estimation model of fuel consumption for the passenger cars in Korea has been developed by considering the road condition. First, the relationship between vehicle speed and fuel consumption that is used to calculate the vehicle operating cost for investment evaluation of transportation facility and the initial feasibility study of road construction was investigated. Second, with the consideration of road roughness, fuel consumption of the passenger car was measured. From the measurement, it was found that fuel consumption increased by $80m{\ell}$ per 100km driving as the roughness increased by 1m/km. Therefore, it is recommended that for the economic analysis of road design and management, the fuel consumption should be a function of road roughness.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.101-114
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• 2006

Recently due to the increase of cars and city life, the traffic congestion has worsened. It Is particularly worse in the center of the metropolis. Within the general public means, the public transport buses have the advantage of being more cheap, accessible and mobile. But as there is no separate lane for buses, the collision of cars and buses are creating damage to public service. In order to solve this situation, the bus priority signal system has been introduced to reduce the bus travel time and improve its services. The purpose of this study is to establish bus priority signal algorithm which builds bus efficiency under the real-time traffic signal control system and to analyze the effect of it. As the green time was calculated against real time (under the real-time traffic signal control system), compared to existing bus priority signal there was a reduction in cross street loss. The modified cycle was used to maintain signal progression. A case study was carried out using VISSIM simulation model. In result of this study, we found that there was a decrease in bus travel time despite some evidence of car delays and compared to existing bus priority signal the delay of dishonor could be reduced dramatically. The analysed result of person delay using MOE, is that there is evidence that when bus priority signal is in effect, the person delay is reduced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.92-104
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• 2017

Previous management for speed in road traffic system was aimed only to the improvement of mobility and safety. However, consideration for the aspect of environment and energy consumption efficiency was valued less than the former ones. Nevertheless, economical damage scope caused by climate change has been increasing and it is estimated that environmental value will be increased because of the change of external circumstances. In addition, policy for reducing carbon emission in transportation system was assessed as insufficient in improving the condition of traffic road since it only focused on the transition of private vehicle into public transportation and development of eco-friendly car. Now it is the time to prepare for the adaptation strategy and precaution for the increased number of private vehicle in Korea. For this, paradigm shift in traffic operation which includes the policy not only about the mobility but also about caring environment would be needed. It is needed to be able to monitor the actual amount of greenhouse gas in real time to reduce the amount of emitted greenhouse gas in the aspect of traffic management. In this research, a methodology which can build on-line greenhouse gas emission monitoring system by using real time traffic data and predicting the circumstance in next 5 minutes was suggested.