• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.08a
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• pp.137-153
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• 2000

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.3
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• pp.66-78
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• 1995

In this paper, we address vehicle modeling and dynamic analysis of four wheel steering systems (4WS). 4WS is one of the devices used for the improvement of vehicle maneuverability and stability. All research done here is based on a production vehicle from a manufacturer. To study actual system response, a three dimensional, full vehicle model was created. In past research of this type, simple, two dimensional, bicycle vehicle models were typically used. First, we modelled and performed a dynamic analysis on a conventional two wheel steering(2WS) vehicle. The modeling and analysis for this model and subsequent 4WS vehicles were performed using ADAMS(Automatic Dynamic Analysis of Mechanical Systems) software. After the original vehicle model was verified with actual experiment results, the rear steering mechanism for the 4WS vehicle was modelled and the rear suspension was changed to McPherson-type forming a four wheel independent suspension system. Three different 4WS systems were analyzed. The first system applied a mechanical linkage between the front and rear steering mechanisms. The second and third systems used, simple control logic based on the speed and yaw rate of the vehicle. 4WS vehicle proved dynamic results through double lane change test.

• 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 Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.79-87
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• 1999

For its simplicity and cost effectiveness in implementation, the Inverted DGPS is well suited for some specific applications like automatic vehicle location systems, where the monitoring station needs accurate position of the vehicles in the street. In the Inverted DGPS, the user sends its GPS position and associated satellite informations to the reference station, and the corrections are made at the reference station to get differentially corrected user position. A fundamental requirement in IDGPS is that the user and the reference station must use the same satellites when the corrections are made. But in practice, it is not often satisfied. Inverted DGPS is also suffered from performance degradation as the baseline become large like DGPS. IDGPS system using multi-reference station can resolve this problem. In this paper a simple multi-reference IDGPS algorithm is proposed and some experiments and analysis are peformed. Experiment results show that IDGPS can achieve the positioning performance as accurate as the DGPS can provide.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.137-146
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• 2002

In this paper, a path generation algorithm that uses sensor scannings is described. A scanning algorithm for recognizing the ambient environment of the Automatic Guided Vehicle (AGV) that uses the information from the sensor platform is proposed. An algorithm for computing the real path and obstacle length is developed by using a scanning method that controls rotating of the sensors on the platform. The AGV can recognize the given path by adopting this algorithm. As the AGV with two-wheel drive constitute a nonholonomic system, a linearized kinematic model is applied to the AGV motor control. An optimal controller is designed for tracking the reference path which is generated by recognizing the path pattern. Based on experimental results, the proposed algorithm that uses scanning with a sensor platform employing only a small number of sensors and a low cost controller for the AGV is shown to be adequate for path generation.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.216-217
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• 2005

This paper presents an integrated navagation control concept for underwater vehicles under high speed navigation circumstance. First of all, in order to control an underwater vehicle with respect to automatic navigation, an integrated navigation control method is suggested in view of synchronous control for course keeping, diving and depth control. An exact nonlinear model equation with six-degree-of-freedom is derived for control algorithm. To identify various hydrodynamic coefficients of the equation, an experimental approach is introduced and results are demonstrated for MANTA type model.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.434-443
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• 2008

This paper develops a novel automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering rate for the output. It localizes the vehicle by using only external sensors - a vision sensor and ultrasonic sensors. Then it automatically learns an optimal fuzzy if-then rule set from the training data, using an evolutionary fuzzy system. Furthermore, it also finds the green zone for the ready-to-reverse position in which parking is possible just by reversing. It has been tested on a 4-wheeled Pioneer mobile robot which emulates the real vehicle.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.503-508
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• 2002

According to passengers gain and headway's contraction, railway vehicle is required quick and correct running. The importance of ATC device was increased gradually, and also is acting important role in safe train running and efficient use in this reason. Now, railway vehicle that is manufactured or is remodeled are designed to most automatic driving system, and ATC device design direction than other device of railway vehicle influences to whole system in this reason. Also, according as system becomes complicated gradually, importance of fault tracing function fur ATC device is emphasized gradually, and in this reason research about efficient fault tracing method is to act important role heightening reliability of ATC device. In this document, that analyzing about result through examination of automatic train operation system of localization model ATC device(SG-100) and application example, and do so that investigate about efficient fault Bracing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2074-2079
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• 2008

This paper presents a software toolbox with $Matlab^{(R)}$ developed for the various performance analysis of an automatic guidance system of the Bimodal Tram. The Bimodal Tram is a new kind of transportation vehicle which could be an all-wheel steered multiple-articulated vehicle. This vehicle has to be equipped with an automatic guidance, traction/braking, and docking system, In the stage of developing such a system, its validities and performances should be verified under various operation conditions. For the purpose of doing these things through simulation, this toolbox has been developed and demonstrated well by applying it to the KRRI model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1059-1068
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• 2016

The current operation method for the AVC (Automatic Vehicle Classification) equipment does not generate vehicle speed, traffic volume and vehicle type information when part of the sensors has failed. Inefficiency of current methods would not use the collected data from the normal sensor. In this study was conducted research on the calculating method at the traffic volume and vehicle speed in the sensor failure AVC equipment. The failure situation of the sensor was classified into 4 types. Calculating the traffic volume and vehicle speed information for each type, and accuracy of these informations were analyzed. Analysis results, traffic volume was possible to calculate a highly accurate value (accuracy: 100%, 98%, 97%). In the case of speed, the accuracy of the calculated speed value reaches a level that can be accepted sufficiently (RMSE value is less than 16.8). So, using the methodology proposed in this study are expected to be able to increase the operational efficiency of the AVC equipment.