• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.320-325
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• 1998

Underwater robotic vehicles (URVs) have been an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system becomes one of the most critical subsytems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. In this paper a new type of fuzzy model-based controller based on Takagi-Sugeno-Kang fuzzy model is designed and applied to the control of of an underwater robotic vehicle. The proposed fuzzy controller : 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule ; 2) can guarantee the stability of the closed-loop fuzzy system ; 3) is relatively easy to implement. Its good performance as well as its robustness to the change of parameters have been shown and compared with the re ults of conventional linear controller by simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.82-86
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• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.30-36
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• 2009

Dedicated Short Range Communication (DSRC) systems in urban areas are used to collect traffic information from vehicles and to provide vehicles with information received from Roadside Equipment (RSE) having a range of 100 meters (m). However, it is not practical to use RSE with a range of 100 m for express highways. In this paper, we expand the standard cell coverage of RSE to 300 m, and adopt fixed relays to cover sites that cannot communicate with the RSE. We demonstrate that the system using the fixed relays is more economical than using only RSE.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.217-223
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• 2015

Autonomous driving is no longer atechnology of the future since the development of autonomous vehicles has now been realized, and many technologies have already been developed for the convenience of drivers. For example, autonomous vehicles are one of the most important drive assistant systems. Among these many drive assistant systems, Cruise Control Systems are now a typical technology. This system constantly maintains a vehicle's speed and distance from a vehicle in front by using Radar or LiDAR sensors in real time. Cruise Control Systems do not only serve their original role, but also fulfill another role as a 'Driving Safety' measure as they can detect a situation that a driver did not predict and can intervene by assuming a vehicle's longitude control. However, these systems have the limitation of only focusing on driver safety. Therefore, in this paper, an Intelligent Cruise Control System that utilizes the path planning method and GIS is proposed to overcome some existing limitations.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.1-8
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• 2014

In recent years, much attention has been paid to the development of intelligent vehicles that integrate automotive technology into the information technology, with the aim of improving user friendliness and stability. The representative function is a autonomous driving and a cruise control. In designing such vehicles, it is critical to address the real-time issues (i.e., real-time vehicle control and timely response). However, previous research excluded the real-time scheduling. We develop a model car with unmanned cruise control, design the real-time scheduler using cyclic executive to easily adapt the model car, and provide some insight into potential solutions based on various experiments.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.9
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• pp.955-960
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• 2011

This study was aimed at investigating the applicability of energy harvesting technologies, which are regarded as new and renewable energy sources for real-time/wireless monitoring of intelligent railroad vehicles. The surrounding energy generated in a normal operating environment was monitored using a high-speed railroad vehicle in operation. This monitoring was performed in an attempt to evaluate the effectives of energy harvesting and the applicability of energy-harvesting-monitoring technologies under the conditions in which thermal energy and vibration energy are generated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.140-146
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• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.1-8
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• 2013

Recently, the automotive technology has developed with electronics and information technology as convergence technology while vehicles had been regarded as machines. Moreover, vehicles are becoming more intelligent and safer devices, assembly of advanced technologies by customers' demand. Even though all of installations of vehicle have attracted as diverting devices, it cause drivers' mistakes like delay of response on traffic condition. Here, we proposed the Field Operational Test (FOT) environment which could be used as driving and road conditions collector(Vehicle motion, Traffic condition, Driver input, Driver state, etc.) for researches about Driver Friendly Intelligent System(SCC, LDWS, etc.), Human Vehicle Interface(Driving Workload, etc.) and Economic Drive Model. Furthermore driving patten and fuel consumption patten of drivers were analyzed by measured data and direction of future research was suggested.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.722-728
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• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.161-167
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• 2012

This research deals with generating via points for autonomous navigation on a roadway for unmanned vehicles. When a vehicle plans a path from a starting point to a goal point, it should be able to map out which lane on which road it passes by. For this purpose, we should organize positional information of roads and save it as a database. This paper presents methods to save the database and to plan a shortest path to the goal by generating via points in consideration of the moving direction and the lane directions. Then we prove that the proposed algorithm can find the optimal path on the road through simulations.