• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.889-893
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• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.1-6
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• 2022

In this research, we suggest a real-time tele-driving system for unmanned fire truck control using the LTE communication system. The operator located in the safe area could drive the unmaned fire truck by implementing the secure tele-operation in case of the emergencies and disaster situation. A prototype of the unmaned fire truck was developed with a fire canon, a high pressure pump, a ball valve and a horse reel. The effect of time delay and FPS was quantified depending on the image sizes and the effective system for realtime tele-operation was suggested. To verify the suggested system, the test was performed between an operator and an unmanned fire truck which is approximately 30km apart. In this research, the immersion tele-driving system is suggested for real-time fire suppression with a 120ms time delay using LTE communication.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.239-242
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• 1998

A new real time sound field visualization technique is introduced in this study using PIV(Particle Imaging Velocimetry) technique. Small particles of which density is small enough to follow up the air flow are used for sound visualization. When the driving frequency is in the vicinity of the resonance frequency of the simplified 2-dimensional muffler system, an acoustic streaming is shown and of which velocity distribution is obtained through PIV technique. It is experimentally proved that the present technique is able to visualize and quantify the sound field's energy flow.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1036-1042
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• 2013

In this paper, an elderly assistance system is developed based on Xenomai, a real-time development framework cooperating with the Linux kernel. A Kinect sensor is used to recognize the behavior of the elderly and A-star search algorithm is implemented to find the shortest path to the person. The mobile robot also generates a trajectory using a digital convolution operator which is based on a Bezier curve for smooth driving. In order to follow the generated trajectory within the control period, we developed real-time tasks and compared the performance of the tracking trajectory with that of non real-time tasks. The real-time task has a better result on following the trajectory within the physical constraints which means that it is more appropriate to apply to an elderly assistant system.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.24-32
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• 2007

Variable message sign (VMS), which is used for providing real-time information on traffic conditions and accident occurrences, is one of the important components of intelligent transportation systems. It is essential that the scheme of VMS message phase and duration should be designed with the consideration of drivers' message reading time that will be depended on various causal factors, such as the amount of VMS messages, drivers' travel speed, and geometric conditions. However, there have been not much efforts to explore the relationships between the drivers' message reading time and the above causal factors. Driving simulator experiments were conducted to obtain drivers' message reading time with respect to the amount of VMS messages, drivers' travel speed, and different geometric conditions. Regression modeling techniques were applied to develop an estimation model for drivers' message reading time. Probabilistic outcomes of the proposed model would be greatly utilized to design proper VMS message phase and duration.

• Journal of ILASS-Korea
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• v.21 no.1
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• pp.1-6
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• 2016

A gasoline injector rig which can measure cumulative injected fuel mass under a vehicle driving condition was developed. The measurement system consists of an engine control unit (ECU), data acquisition (DAQ) and injected fuel collection system using loadcells. By supplying reconstructed sensor signals which simulate the real vehicle's sensor signals to the ECU, the ECU drives injectors as if they were driven in the vehicle. The vehicle's performance was computer simulated by using $GT-Suite^{(R)}$ software based on both engine part load performance and automatic transmission shift map. Throttle valve position, engine and vehicle speed, air mass flow rate et al. were computer simulated. The used vehicle driving pattern for the simulation was FTP-75 mode. For reconstructing the real vehicle sensor signals which are correspondent to the $GT-Suite^{(R)}$ simulated vehicle's performance, the DAQ systems were used. The injected fuel was collected with mess cylinders. The collected fuel mass in the mess cylinder with elapsed time after starting FTP-75 driving mode was measured using loadcells. The developed method shows highly improved performance in fast timing and accuracy of the cumulative injected fuel mass measurement under the vehicle driven condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.174-183
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• 2005

A train driving requires to n the fixed distance within given time, and it is desirable to consume low energy if necessary. Reducing energy consumption depends on the train operation modes by either manual or automatic operation. In this article, an operation to reduce energy consumption by changing modes of train operation by a driver without changing the train operation requirement is investigated. The powering model, braking model and consumed energy calculation model are developed, then simulated by using a Matlab software. The accuracy of the train dynamic model established by the simulations is verified by comparing with the real experimental data. Several simulations by various operations in the real track are executed, then the desirable pattern of train driving is found.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.3
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• pp.17-23
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• 2011

To estimate fuel consumption of a vehicle, a car can be tested on chassis dynamometer. In this case, test causes a lot of time and money. To predict the fuel efficiency of vehicles in the design stage or early stage of development, the development of computer simulation model is necessary. Using simulation to predict the fuel consumption, the driving model which consists of time-velocity profile and time-grade profile is necessary In this study, vehicle model is developed in MatLab/simulink to estimate real driving fuel consumption rate with time-velocity profile, time-shift gear profile and time-grade profile. Vehicle model consists of driver model, engine model, power train model, and so on. On-road vehicle tests to verify the vehicle model are carried out for analyzing the result of simulation and comparing with those of the experiments.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_1
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• pp.521-531
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• 2022

This study proposed a new approach to intelligent control of a mobile robot system by back properpagation based on multi-layer neural network. A experiment result is given in which some artificial assumptions about the linear and the angluar velocities of mobile robots from recent literature are dropped. In this study, we proposed a new thinique to impliment the real time conrol of he position and velocity of mobile robots. With the proposed control techinique, mobile robots can now globally follow any path such as a straight line, a circle and the path approaching th toe origin using proposed controller. Computer simulations are presented, which confirm the effectiveness of the proposed control algorithm. Moreover, practical experimental results concerning the real time control are reported with several real line constraints for mobile robots with two wheel driving.