• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.511-514
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• 2011

Recently, devices such as smartphone and vehicle blackbox and EDR(Evern Data Recorder knowed automotive real-time control and driving data to use OBD-2(in-vehicle network). when devices receive vehicle driving data, communication way use each Wifi, Bluetooth. but if user and driver change device to use OBD-2 connect, the device differ communication network way. and driver buy and change OBD-2 connect. In this paper, to remedy one's shortcomings, there integrate Bluetooth and Wifi network module and design integrability hardware as any another device know vehicle real-time control and driving data with one integrability connect.

• Resources Recycling
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• v.10 no.3
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• pp.3-13
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• 2001

The Korean Auto industry has developed remarkably over the past 30 years. In 2000 alone, Korea produced 3.11 million vehicles, and the number of vehicles registered surpassed the ten million mark. As the number of vehicles registered in Korea has increased, yew after you, a rising number of cars have been scrapped. In 2000, a total of 455,592 automobiles were scrapped, up dramatically from only 101,158 in 1989. The system for handling of ELV(End-of-Life Vehicles) in Korea is governed by the "Motor Vehicle Control Act". The Act places the responsibility for vehicle scrapping directly on the vehicle owners. h vehicle owner can only can eel a vehicle registration after he gets a certificate from an authorized vehicle dismantler showing that his vehicle was properly scrapped according to the law. The take-back rate of ELV reaches nearly 100% in Korea. The vehicle scrapping process in Korea is very similar to those in other countries. fluids such as fuels and oils are first removed, and recyclable parts are collected and separated. Engines and transmissions are dismantled and recycled for use as raw material. Plastics, which are not easily reused, are generally treated as industrial wastes. The "Motor Vehicle Control Act" prohibits reuse of certain parts in order to guarantee the safety of the used auto parts. However, some restrictions on the reuse of auto parts have recently been eased to promote recycling. In this paper, additionally, car recycling policy of the foreign countries such as Japan, Germany and EU were reviewed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.800-813
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• 2021

With the advent of 5G communications, internet of vehicles technology has been widely used in vehicles. Then the dynamic spread of information between vehicles began to come into focus with more research. It is well known that the identification of nodes with great spread influence has always been a hot topic in the field of information spreading. Most of the existing work measures the propagation influence by degree centrality, betweenness centrality and closeness centrality. In this paper, we will identify influential vehicle nodes based on the mobility characteristics of vehicles to explore the information spreading between vehicles in VANETs. Different from the above methods, we mainly explore the influence of the radius of gyration and vehicle kilometers of travel on information spreading. We use a real vehicle trajectory data to simulate the information transmission process between vehicles based on the susceptible-infected-recovered SIR model. The experimental results show that the influence of information spreading does not enhance with increasing radius of gyration and vehicle kilometers of travel. The fact is that both the radius of gyration and the distance travelled have a significant influence on information spreading when they are close to the median. When the value of both is large or small, it has little influence on information spreading. In view of this results, we can use the radius of gyration and vehicle kilometers of travel to better facilitate the transmission of information between vehicles.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.182-187
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• 2007

The accuracy of the results of the rail vehicle dynamic model is dependent on the realism of the track input to the model. An important part of the track input is the irregularities that exist on actual track. This study presents a modeling method for creating track data with the irregularities for use as the input to VAMPIRE, a rail vehicle dynamic analysis program. The characteristics of the measured track data using the mid chord system has been studied and examined the method to create track data with the measured data to apply in the vehicle dynamic analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.209-212
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• 2005

The look-ahead preview control with the use of limited bandwidth active suspensions is presented. Both a linearized racked vehicle model and a complex nonlinear model based on a commercial multibody dynamic program are used to verify the performance of preview control. The performance of the preview control system is evaluated on the ride quality which is estimated from the acceleration of the driver position. Due to the practical advantages associated with the use of limited bandwidth active control in comparison with full bandwidth systems, the results are considered important to the future development of active tracked vehicle suspensions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2347-2352
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• 2011

driver for safety always check the status of their vehicle, and it is essential to understand. But if you want to know the status of the driver of the vehicle in specialist referral time and money because it costs the operator shall be paid.IT technoligy with the development of the various features of your phone to check the status of the vehicle was able to do. However, the car' existing phone system, car diagnostic expertise must be learned because it will reveal the status of the vehicle do not have the expertise to not highlight the need for diagnostic. To reflect these points in smartphone users to easily use their own vehicles at a time to determine the status of a system that is required. In this paper, OBD-II protocol conversion WiFi OBD-II connector, retrieving information from the driver of the vehicle replacement cycle of consumables required vehicle inspection, vehicle problems in real-time diagnostic information to the user ease of use shows the iPhone implementation in the automotive supply was implemented based on the smartphone.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.12
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• pp.1099-1103
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• 2013

A combat vehicle needs to have an air-conditioning unit. Accordingly, new combat systems have tended to apply an integrated heating, cooling, and ventilating system. The air conditioning unit used depends on the combat vehicle's purpose of use. In this study, we studied an air-conditioning unit for an armored combat vehicle as a special use and military specification and tried to improve the air-conditioning unit's performance.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.119-126
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• 2022

This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibration-induced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.609-620
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• 2016

Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.