• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.1
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• pp.1-9
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• 2015

To satisfy stricter $NO_X$ emission regulations for light- and heavy-duty diesel vehicles, a control algorithm needs to be developed based on a selective catalytic reaction (SCR) dynamics model for chemical reactions. This paper presents the development and validation of a SCR dynamics model through test rig experiments and MATLAB simulations. A nonlinear state space model is proposed based on the mass conservation law of chemical reactions in the SCR dynamics model. Experiments were performed on a test rig to evaluate the effects of the $NO_X$ and $NH_3$ concentrations, gas temperature, and space velocity on the $NO_X$ conversion efficiency for the urea-SCR system. The parameter values of the proposed SCR model were identified using the experimental datasets. Finally, a control-oriented model for an SCR system was developed and validated from the experimental data in a MATLAB simulation. The results of this study should contribute toward developing a closed-loop control strategy for $NO_X$ and $NH_3$ slip reduction in the urea-SCR system for an actual engine test bench.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.3037-3047
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• 2000

This paper describes a method of tracking a close leading vehicle by color image processing using the pairs of tail and brake lights. which emit red light and are housed on the rear of the vehicle in stop-and-go traffic condition. In the color image converted as an HSV color model. candidate regions of rear lights are identified using the color features of a pair of lights. Then. the pair of tailor brake lights are detected by means of the geometrical features and location features for the pattern of the tail and brake lights. The location of the leading vehicle can be estimated by the location of the detected lights and the vehicle can be tracked continuously. It is also possible to detect the braking status of the leading vehicle by measuring the change in HSV color components of the pair of lights detected. In the experiment. this method tracked a leading vehicle successfully from urban road images and was more useful at night than in the daylight. The KAV-Ill (Korea Autonomous Vehicle- Ill) equipped with a color vision system implementing this algorithm was able to follow a leading vehicle autonomously at speeds of up to 15km!h on a paved road at night. This method might be useful for developing an LSA (Low Speed Automation) system that can relieve driver's stress in the stop-and-go traffic conditions encountered on urban roads.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.187-196
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• 2011

Induction motors play a vital role in aeronautical and automotive industries so that many researchers have studied on developing a fault detection and classification system of an induction motor to minimize economical damage caused by its fault. With this reason, this paper extracts robust feature vectors from the normal/abnormal vibration signals of the induction motor in noise circumstance: partial autocorrelation (PARCOR) coefficient, log spectrum powers (LSP), cepstrum coefficients mean (CCM), and mel-frequency cepstrum coefficient (MFCC). Then, we classified different types of faults of the induction motor by using the extracted feature vectors as inputs of a neural network. To find optimal feature vectors, this paper evaluated classification performance with 2 to 20 different feature vectors. Experimental results showed that five to six features were good enough to give almost 100% classification accuracy except features by CCM. Furthermore, we considered that vibration signals could include noise components caused by surroundings. Thus, we added white Gaussian noise to original vibration signals, and then evaluated classification performance. The evaluation results yielded that LSP was the most robust in noise circumstance, then PARCOR and MFCC followed by LSP, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.22-32
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• 2010

Increasingly advanced Information Technology (IT) has changed the operator so as to create more diversified and advanced traffic information demand. To deal with the changing demand in private sector, a concept of on-demand traffic information has been rapidly introduced. However VMS, a product of the first generation of ITS, which was designed to provide the unspecified individuals during driving the car with the basic level of traffic information by the public failed to actively change itself in such a changing pattern. This study was intended to describe the VMS system (tentatively, FM-VMS) which was further developed to accommodate the needs favoring the sophisticated PDA with the public role of providing the unspecified individuals with the equal information. FM-VMS introduced in this study is the device designed to transmit the voice and message to the drivers through the radio information device mounted on a car. A core technology is, unlike FM-DARC and RDS, the Water Making technology which directly inserts the digital signal into FM frequency in use. It's been currently used for broadcasting and security purpose. A detection rate as a result of testing FM-VMS system using Water Making technology was 90% or more in voice and message within 20m from test VMS. When a public-developed VMS information could be transmitted using FM frequency to the relatively vulnerable users (vulnerable to traffic information) in voice on a real-time basis to provide the regional traffic information, and furthermore, VMS message could be received through radio liquid using FM frequency only, it would obviously bring about the innovation in ITS as well as pave the way for creating the new added value down the road.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.688-697
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• 2014

In this study, electrode bonding technology needed for high density of rechargeable battery is studied, which is recently researched for electric vehicle, the small leisure vessel. For the alternative overcoming the limit of stacking amount able to be stacked by conventional ultrasonic welding, the low temperature bonding method, eligible for minimum of degeneration of chemical activator on the electrode surface which is generated by thermal effect as well as the increase of conductivity and tension strength caused by electrode bonding using filler metal, not using conventional direct heating on the electrode material method, is studied. Specifically to say, recently used more generally the ultrasonic welding and spot welding method are not usable for satisfying stable electric conductivity and bonding strength when much electrode is stacking bonded. If the electrical power is unreasonably increased for the welding, due to the effect of welding temperature, deformation of electrode and activating material degeneration are caused, and after the last packaging, decline of electrical output and generating heat cause to reduce stability of battery. Therefore, in this study, induction heating system bonding method using high frequency heating and differentiated electrode method using filler metal pre-treatment of hot dipping are introduced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2604-2611
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• 2013

The Personal Rapid Transit(PRT) system has been highly interested in future transportation developments due to its on-demand and optimized door-to-door transport capability. However, the major impediments to the commercialization of PRT are the high cost for construction of infrastructures as opposed to the small transport capacity and difficulty in defining the role of PRT in building a balanced transportation system. In this study, the vertical transfer device for the PRT vehicle is developed to provide more flexible and better compatible urban mobility services between means of transportation, which is expected to meet particular demands in a particular environment. This apparatus was initially designed based on the basis of vertical circulating conveyors with steel chains, which is frequently used in logistics. Its advantages are capable of the non-stop loading and reduced head-way time. Most importantly, it was intensified by the additional idea to ensure the stable and reliable transfer of the PRT vehicle fully loaded with passengers. The 1/10-scale prototype was successfully tested to demonstrate a fundamental mechanism of vertical transfer and identify unexpected user requirements prior to a real manufacturing process.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.18-25
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• 2016

As more people have cars, the threat of traffic accidents is posed on men and women of all ages. The main culprit of traffic accidents is driving while intoxicated or drowsy. The method to recognize and prevent the cause of traffic accidents is to use lane detection. In this study, a total of 4,000 frames (day image: 2,900 frames, night image: 1,100 frames) were used to test lane detection. According to the test, in the case of day image, when the threshold of Sobel edge detection technique was detected with second-order differential equation, there was the highest candidate lane detection rate which was 86.1%. In the threshold of Canny edge detection technique, the highest detection rate of 88.0% was found at Low=50, and High=300. In the case of night image, the threshold of Sobel edge detection technique, when horizontal calculation and vertical calculation had second-order differential equation, and when horizontal-vertical calculation had 1.5th-order differential equation, there was the highest detection rate which was 83.1%. In the threshold of Canny edge detection technique, the highest detection rate of 89.9% was found at Low=50, and High=300.