• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.148-156
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• 2014

The objective of this study is to compare NOx emissions from light duty diesel vehicles measured from on-road tests that conducted under various driving routes and seasonal conditions. We measured real-driving NOx emissions using PEMS, portable emissions measurement system, under the urban, rural and motorway road traffic conditions. On-road tests were repeated at summer, fall and winter season. The accumulated driving distance is more than 1,200 km per each vehicle. Route average NOx emission factors were compared among nine route-season combinations. The emission characteristics of each combinations were investigated using time series mass emission rates and vehicle operation-based emission rates and activities, which is based on U.S. EPA's MOVES model. Most concerned route-season combination is "urban road condition at summer", which shows two to eleven times higher NOx emissions than other combinations. The emission rates and activities under low speed operating conditions should be managed in order to reduce urban-summer NOx. From a NOx control strategy perspective, the exhaust gas recirculation, EGR, is observed to be properly operated under wide range of vehicle driving conditions in Euro-5 vehicles, even if the air conditioner turns on. In high power demanding conditions, the effect of overspeeding could be more critical than that of air conditioner activation.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.734-744
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• 2013

In this study, the telematics device was installed on the car (OBD-II) to collect the information on the operation conditions from each sample vehicle. Based on the information the domestic driving pattern was analysed and the ratio of cold start length was estimated. As a result of analysis for driving pattern, we found a difference in the frequency of driving on the hourly or seasonal basis. Then, the driving pattern of the rush hours, weekdays, and weekends could be derived. Also, from the study, an average of 2.22 times per day occurred in a single trip and average driving distance for the trip was 15.72 km. In addition, the proportion of cold start length was analyzed to be 16.11%. The seasonal cold start length has big difference from season to season (Winter 26.63%, Summer 8.22%, Intermediate 12.65%). There was an inverse relationship between the outside temperature and ratio of cold start length. In order to improve the accuracy of the cold emission estimation, it is necessary to apply domestic ratio of cold start length that driving pattern and temperature in Korea is reflected.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.107-108
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• 2011

Since the development of railway technology, the current urban Railway the first train line in the country for safe operation control automatic/unattended operation, automatic train operation equipment available (ATO) on time and reliable operation has introduced. ATO Automatic operation controlled by the value (Target velocity) and the feedback value (Actual velocity) by the error between the backing and braking of the train by repeated low energy efficiency. In this paper, given a fixed distance stations between time operation with minimal energy in the driving characteristics and driving trains are modeled. Therefore, in line 5 real route time sectional drive straight sections for experimental data analysis / draft Section / curved and section of the train on that line is selected according to the changing driving patterns to minimize the energy optimal driving patterns were presented.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.76-81
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• 1993

This paper presents an Auto-Drive-Guidance System which provides a path to the destination with the shortest driving distance(or time), as well as service information such as the location of gas stations, hospitals, or police stations. This system displays on the monitor screen the best driving path to the destination, points the current car position on the map, informs the driver of current position by voice whenever the car passes well-known places, or displays the map the driver wishes to view. With this system, driving becomes more comfortable, and traffic jams will be greatly reduced. As a result, gasoline consumption will be reduced and so air pollution. The system can also be applied to such areas as communication network, geographic map, and tour information.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1313-1317
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• 2005

This paper presents the overall design, manufacture, and test result of the high capacity (more than 150 Am^2) magnetic torquer for the use of satellite control. To provide an electrical current to the magnetic torquer, the driving electronics is also constructed. The integration and test of the magnetic torquer and its driving electronics are performed via the magnetic field measurement according to the distance and the magnetic torque measurement with torque-meter. To compare the performance obtained from the test results we also perform computer simulation with three-dimensional model.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.848-854
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• 1999

In this paper, we designed and implemented a precise pulse motor controller chip that generates the pulse needed to control step motor, DC servo and AC servo motors. This chip generates maximum pulse output rate of 5Mpps and has the quasi-S driving capability and speed and moving distance override capability during driving. We designed this chip with VHDL and executed a logic simulation and synthesis using Synopsys tool. The pre-layout simulation and post-layout simulation was executed by Compass tool. This chip was produced with 100 pins, PQFP package by 0.8${\mu}{\textrm}{m}$ gate array process and implemented by completely digital logic. We developed the test hardware board of performance and the CAMC(Computer Aided Motor Controller) Agent softwate to test the performance of the pulse motor controller chip produced. CAMC Agent enables user to set parameters needed to control motor with easy GUI(Graphic User Interface) environment and to display the output response of motor graphically.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.92-97
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• 1998

The morpholgies of the wear particles are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify wear debris generated from the machine driving system. The four parameters(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction condition of five values(material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different patter characteristic and recognized the friction condition and materials very well by artificial neural network. We discussed how the network determines differencee in wear debris feature, and this approach can be applied to foreseeability and decisio for moving condition of the Machine driving system.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.36-48
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• 2010

This paper is concerned with stereo vision-based approach to detect obstacles and to generate the path of destination from the start. The hexapod robot in the experiment is cable of walking by legs and driving by wheels simultaneously. The hexapod robot operates under the driving mode normally, and it changes driving mode to walking mode to overcome obstacles using its legs. Disparity map, which is the correlation between two images taken by stereo camera, is employed for calculation of the distance between the robot and obstacles. When the obstacles information is extracted from the disparity map, the potential field algorithm is applied to create the obstacle-avoidance path. Simulator, based on OpenGL, is developed to generate the graphical path, and the experimental results are shown for the verification of the proposed algorithm.

• Explosives and Blasting
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• v.27 no.2
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• pp.42-47
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• 2009

Ground vibrations caused by pile driving or explosive blasting can affect the stability of power line tower and its foundation. Because the characteristics of ground vibrations generally depend on the distances from the blast, the ground vibrations should be controlled by taking the distance into account. In this study, ground vibration levels were measured at the foundation of a power line tower and on ground surface adjacent to the tower. The relationships between the dominant frequencies of the ground vibrations that were measured at both locations were comparatively investigated.