• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.1-8
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• 2019

In December 2017, many collision accidents of small vessels, such as those between oil refineries and fishing boats, occurred near Yeonghung-do in Incheon. In order to prevent marine casualties from small vessels, the government is striving to improve the safety capabilities of ship operators by strengthening education and improving the working environment. They are providing education and refining training regulations for fishermen operating vessels under 5 tons. However, the situation includes certain vulnerabilities. In this study, we propose a collision prevention algorithm for small vessels using the Wireless Access in Vehicular Environments (WAVE) communication system, which is a new communication technique to prevent collisions with small ships. The collision avoidance algorithm used is based on DCPA/TCPA. Research analyses, simulation experiments and questionnaires have been conducted to define the criteria of DCPA/TCPA. As a result, the standard for DCPA was $8(L_a+L_b)$ and for TCPA was 2.5 min. Three different accident cases were selected, and this algorithm was applied to confirm alarm responses at certain times. This algorithm can provide information to the operators of small ships in advance to help them recognize potential collision situations.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.911-916
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• 2008

Impact noise caused by the collision of bodies is difficult to estimate because of the complexity of impact phenomenon. In this study, impact noise is estimated using two different methods when the noise is caused by the vibration due to impact. First, impact noise is analyzed using impact analysis and boundary element analysis. Second, modal expansion technique is applied to the estimation of impact noise. Experiment is carried out to validate the analysis results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.49-57
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• 2011

Random access method for Wibro system is proposed using the Bayesian Technique, which can estimate the number of bandwidth request messages in a frame only based on the number of successful slots. The performance measures such as the maximum average throughput, the mean delay time and the collision ratio are investigated to evaluate the performance of the proposed method. The proposed method shows better performance than the binary exponential backoff algorithm used currently.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1918-1920
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• 2000

In this paper, acoustic signals in GIS were analyzed by using wavelet transform and FFT to distinguish sound source caused by collision of particles and partial discharges. As a result, the analysis using wavelet transform was more accurate than that using FFT. Therefore, wavelet transform was useful technique to analyze the acoustic signals in GIS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1111-1119
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• 2022

Tourism projects through islands in the waters of Sinan-gun became active, and as a result, a total of 13 marine bridges connecting islands were completed. However, the marine bridge constructed in the fairway is dangerous for traffic. Particularly, in the case of the marine bridge connecting two islands, the width of the fairway is extremely narrow, therefore the risk is higher. In this study, we evaluated the risk of collision between marine bridge piers and ships using the IALA Waterway Risk Assessment Program (IWRAP), a risk assessment model for port waterways, based on a maritime traffic survey on the coastal bridge in Sinan-gun. The results, indicated that No.1 Sinan bridge had the highest probability of collision and most of the transit ships were coastal passenger ships. In addition, No.1 Sinan bridge was the place where the most collision accidents occurred among the marine bridge piers in the target sea, and the cause this study was analyzed. An analysis of the satellite images of the sea environment of No.1 Sinan bridge using an image processing method, confirmed that obstacles that could not be seen in the chart existed nearby the bridge. As a result, traffic was observed to be concentrated in one direction, unlike two-way traffic, which is a method of inducing traffic of bridges to avoid obstacles. The risk cause analysis method using the image processing technique of this study is expected to be used as a basic research method for analyzing the risk factors of island bridge in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.31-39
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• 2014

Recently, as Intelligent Transportation System (ITS) and self-driving system become influential in the ground transportation system, automotive radar systems have been actively studied among the various radar systems to implement the vehicle collision detection system and distance measurement system between vehicles. Most of the automotive radars are Frequency Modulated Continuous Wave (FMCW) radar type which can calculate distance and velocity of target by estimating the frequency difference between the transmitted signal and received signal. Therefore, accurate frequency estimation is very important in the FMCW radar system. For this reason, to improve the measurement accuracy of the FMCW radar, Reverse Directional FRI (RD-FRI) Super-Resolution technique which has high frequency estimation accuracy is applied to the FMCW radar system. The feasibility of the proposed technique is evaluated with simulation results and compared with FFT and conventional Super-Resolution techniques. The simulation results show that the proposed technique estimates the frequency with high accuracy and the distance with centimeter accuracy.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.113-123
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• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.1063-1068
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• 2015

In this paper, we propose a collision simulation technique the evaluation of urban trains. We perform simulation that include a dynamics bogie model which represents the dynamic behavior of bogies and a finite-element model that can model crash behavior. We perform simulation in accordance with the 40-mm vertical offset head-on scenario for overriding the evaluation of the EU and domestic crashworthiness regulations. We evaluate the overriding by the vertical displacement of the wheelset using the overriding evaluation standard. Finally, if proposed simulation technique is applied, we can evaluate the overriding for urban-train crashworthiness regulations.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.