• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Journal of Engineering Education Research
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• v.15 no.4
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• pp.48-52
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• 2012

The purpose of this paper is to design and implement the user motion pattern control system for the simulated vehicle. After analyzing the user motion patterns in the system, the patterns are used to control the moving direction of the simulated vehicle such as forward, backward, turn right, turn left etc. The patterns in the system around are sent to the simulated vehicle in real time. In order to execute the suggested user motion pattern control system, the Kinect is used for executing the system. The Kinect recognizes the specified user motion patterns and it transmits the data to the user motion pattern control system. There are nine kinds of the user motion patterns in the system for controlling the simulated vehicle. In addition to this, some sensors are used to detect the condition of the simulated vehicle. GPS is also used to estimate the current location of the simulated vehicle and to obtain the driving information.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• Journal of the Korean Society of Safety
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• v.14 no.4
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• pp.85-92
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• 1999

Vehicle rollover is an important issue for the traffic safety. Rollover can occur from the driver's action, the vehicle characteristics, or the road condition. This study is about the rollover propensity analysis of a jeep vehicle using the steering and braking maneuver, which is the combined result by the driver and the vehicle. Simple equations of roll motion is used to analyze the roll motion and a special purpose vehicle dynamics program is used to simulate the rollover of the jeep vehicle. From the simulation, an incipient rollover motion of the vehicle was found. However, the more complete rollover propensity analysis would require further investigation using roll dynamic sensitivity study.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.2
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• pp.100-105
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• 2011

By adopting HIL(Hardware-in-the-Loop), component characteristics in vehicle environment can be obtained without implementing component in the vehicle. In this paper, when specific motor is adopted as traction motor in hybrid electric vehicle HIL implementation procedures are explained. In order to implement HIL method motor testing. vehicle performance simulator and load characteristic are explained. Vehicle controller used in simulator is directly uploaded in real controller. Especially as a load dynamometer actively controlled motor system is used without connecting conventional mechanical inertia. Motor characteristics are obtained using HIL implementation when test motor is used as a traction motor for parallel hybrid electric vehicle. Proposed method can be used as experimental equipment to educate driving characteristics of hybrid electric vehicle.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• Journal of Mechanical Science and Technology
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• v.16 no.9
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• pp.1166-1174
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• 2002

This paper presents the implementation and vehicle tests of a vehicle longitudinal control scheme for Stop and Go cruise control. The control scheme consists of a vehicle-to-vehicle distance control algorithm and throttle/brake control algorithm for acceleration tracking. The desired acceleration of a vehicle for vehicle-to-vehicle distance control has been designed using Linear Quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. A millimeter wave radar sensor has been used for distance measurement. A stepper motor and an electronic vacuum booster have been used for throttle/brake actuators, respectively. It has been shown that the proposed control algorithm can provide satisfactory performance.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.904-907
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• 2011

Various types of gases and propellants are used in launch vehicle. In order to fulfill the mission of the launch vehicle, the components and systems used in launch vehicle should ensure flawless operation in these environments. The pneumatic test is the test performed using compressed gas to prove requirements of the components and systems. This paper describes the requirements of the gas quality for pneumatic test, leak test method, and pneumatic test of the launch vehicle.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.317-325
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• 2011

Vehicle model validation for the static vehicle testing has been done by comparison of the simulation results and test results and the parameters of the vehicle model to be used in the simulation have been adjusted to reflect the measured behaviour. The vehicle model fort the simulation should be validated by suitable tests and/or practical experience. The static vehicle test used to validate the vehicle model are the weight measurement, the wheel offloading test, the bogie rotational resistance test and the sway test. Finally, the computer simulation model has been validated and using the validated vehicle model the acceptance of the vehicle safety of the resistance to flange climbing derailment at low speed can be examined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.