• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.84-90
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• 2011

In this paper, a VoIP-based voice secure telecommunication technology using the text-independent speaker authentication in the telematics environments is proposed. For the secure telecommunication, the sender's voice packets are encrypted by the public-key generated from the speaker's voice information and submitted to the receiver. It is constructed to resist against the man-in-the middle attack. At the receiver side, voice features extracted from the received voice packets are compared with the reference voice-key received from the sender side for the speaker authentication. To improve the accuracy of text-independent speaker authentication, Gaussian Mixture Model(GMM)-supervectors are applied to Support Vector Machine (SVM) kernel using Bayesian information criterion (BIC) and Mahalanobis distance (MD).

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.373-378
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• 2002

In fuzzy inferencing, most of conventional fuzzy controllers have problems of speed down in floating point operations of fuzzy membership functions in (0,1) as compared with integer operations. Therefore, in this paper, we propose a high-speed fuzzy controller with only integer operations. In this, for fast fuzzy computations, we use a scan line conversion algorithm to convert lines of each fuzzy linguistic term to the set of the closest integer pixels. We also implement a GUI (Graphic User Interface) application program for the convenient environments to modify and input fuzzy membership functions.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.470-476
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• 2001

This paper presents a new algorithm of path planning and obstacle avoidance for autonomous mobile robots with vision system that is working in unknown environments. Distance variation technique is used in path planning to approach the target and avoid obstacles in work space as well . In this approach, the Sobel operator is employed to detect edges of obstacles and the distances between the mobile robot and the obstacles are measured. Fuzzy rules are used for trajectory planning and obstacle avoidance to improve the autonomy of mobile robots. It is shown by computer simulation that the proposed algorithm is superior to the vector field approach which sometimes traps the mobile robot into some local obstacles. An autonomous mobile robot with single vision is developed for experiments. We also show that the developed mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1229-1234
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• 2012

Vehicular communications have been receiving much attention in intelligent transport systems (ITS) by combining communication technology with automobile industries. In general, vehicular communications can be used for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication by adopting IEEE802.11p/1609 standard which is commonly known as wireless access in vehicular environments (WAVE). WAVE system transmits signal in 5.9GHz frequency band with orthogonal frequency division multiplexing (OFDM) signaling. In this paper, we consider physical layer issues in vehicular communications. We first overview the physical (PHY) layer of WAVE standard and properties of 5.9GHz signals, and then physical layer issues to provide reliable communication link are discussed.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.135-142
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• 2018

This paper compares and analyzes advantages and disadvantages of CDMA(code division multiple access) and OFDM(orthogonal frequency division multiplexing) transmission techniques for underwater acoustic channel environments. Computer simulations were carried out in various underwater acoustic channels with varying r.m.s.(root mean square) delay, doppler frequency and the number of multipaths. When r.m.s. delay and doppler frequency are within the tolerance of designed transmission schemes, the computer simulations show that CDMA has better BER performance than that of the OFDM. However, when the doppler frequency exceeds the tolerance, BER performance of the CDMA decreases.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.86-91
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• 2012

To provide high voice quality of real-time voice communication based on telematics exposed to various noise environments, the noise reduction algorithm with low computing load is required to effectively remove the noise. In this paper, we propose a noise reduction algorithm based on Mel-Filter and illustrate the proposed algorithm comparing with conventional noise reduction algorithms. As a experimental result that evaluates the performance of the noise reduction algorithms under the car and babble noise environments, the proposed noise reduction algorithm has the lower computing load with the similar PESQ score compared to the conventional noise reduction algorithms. It proves that the proposed noise reduction algorithm can efficiently remove the noise in mobile telematics.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.36-46
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• 2011

It is thought traffic flow management under the ubiquitous transportation system has great potential in view of individual vehicle data availability and V2V, V2I two-way communication environments. However, it is expected that deployment of the ubiquitous transportation system takes some time. Therefore it is necessary to evaluate the feasibility of the algorithm under the ITS environment. The speed management algorithm proposed in the previous research is revised to fit for the ITS data collection and information provision environment. And the feasibility of the algorithm is evaluated through simulation experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.293-298
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• 2000

In fuzzy expert systems or database systems that have volumes of fuzzy data or large fuzzy rules, the inference time is much increased. Therefore, a high performance parallel fuzzy computing environment is needed. In this paper, we propose a parallel fuzzy inference mechanism in parallel computing environments. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input input vector to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of fuzzy or data, the parallel fuzzy inference algortihm extracts effective and achieves and achieves a good speed factor.