• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.1
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• pp.17-22
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• 2013

If we were in a head-on or crossing situation with a target ship and did not know the target ship's intention to change her course, we might be confused about our decision making to change our course for collision avoidance and be in a danger of collision. In order to solve these problems, we need to develop an automatic system which enables mariners to easily detect a change in the target ship's course and efficiently avoid being on a collision course. In this paper, we proposed an early detection method on altering course of a target ship using the steering wheel signal. This method will contribute to the reduction of collision accidents and also be used to the VTS system and the analysis of marine accidents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1732-1739
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• 2004

In this paper, we proposed a visualization system with ANN algorithm that traits the motion of particles that move colliding in the water, where we got a great deal of variable information and predicts the distribution of particles according to the flowing of water and the pattern of their precipitation. We adopted ART2 to detect sensitively the collision between particles in this visualzation. Various particles and their mutual collision influencing the force such as buoyancy force, gravitational force, and the pattern of precipitation are considered in this system. Flowing particles whose motion is changed with the environment can be visualized in the system presented here as they are in real water.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.476-483
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• 2021

In order to maintain the safety of the airspace with ever increasing traffic volume, it is necessary to thoroughly analyze the collision risk with the current data. In this study, collision risk analysis was conducted using Detect and Avoid (DAA) Well-Clear (DWC) metrics, risk induces developed for the DAA systems of unmanned aerial vehicles. All flights in year 2019 that flew within the Incheon Flight Information Region (FIR) boundary were analyzed using the recorded Automatic Dependent Surveillance-Broadcast(ADS-B) data. High risk regions as well as trends by airports and seasons were identified. The results indicate that the risk is higher around the congested area near Incheon International Airport and Gimpo International Airport. Seasonally, the risk was highest in August that coincides with the Summer vacation period. The result will be useful for the baseline data for various aviation safety enhancement activities such as revision of routes and procedures and training of the field specialists.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.427-433
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• 2022

Obstacle detection, collision recognition, and avoidance technologies are required the collision avoidance technology for UAVs. In this paper, considering collinear multiple static obstacle, we propose an obstacle detection algorithm using LiDAR and a collision recognition and avoidance algorithm based on CPA. Preprocessing is performed to remove the ground from the LiDAR measurement data before obstacle detection. And we detect and classify obstacles in the preprocessed data using the K-means clustering algorithm. Also, we estimate the absolute positions of detected obstacles using relative navigation and correct the estimated positions using a low-pass filter. For collision avoidance with the detected multiple static obstacle, we use a collision recognition and avoidance algorithm based on CPA. Information of obstacles to be avoided is updated using distance between each obstacle, and collision recognition and avoidance are performed through the updated obstacles information. Finally, through obstacle location estimation, collision recognition, and collision avoidance result analysis in the Gazebo simulation environment, we verified that collision avoidance is performed successfully.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.609-620
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• 2016

Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.164-170
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• 2013

The latest vehicle yields a superior safety and reduction of driving burden by monitoring the driving state of vehicle and its environment with various sensors. To detect other vehicles and objects of the rear left and right-side blind spot area of driver, provide the information about a existence of objects inside the blind spot, and give a signal to avoid collision, this study proposes the intelligent outside rear-view mirror system. This study proposes SILS system with PreScan and Matlab/Simulink to verify practical applicability of developed BSDS. PreScan yields realistic driving environments and road conditions and vehicle model dynamics and collision warning is controlled by Matlab/Simulink.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1203-1222
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• 2012

To provide active notification and enhance drivers'awareness of their surroundings, a vision-based collision warning system that detects and monitors surrounding vehicles is proposed in this paper. The main objective is to prevent possible vehicle collisions by monitoring the status of surrounding vehicles, including the distance to the other vehicles in front, behind, to the left and to the right sides. In addition, the proposed system collects and integrates this information to provide advisory warnings to drivers. To offer the correct notification, an algorithm based on features of edge and morphology to detect vehicles is also presented. The proposed system has been implemented in embedded systems and evaluated on real roads in various lighting and weather conditions. The experimental results indicate that the vehicle detection ratios were higher than 97% in the daytime, and appropriate for real road applications.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.971-975
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• 2005

In this study, a car-door-controlled collision protection system using proximity sensor is proposed and its preliminary analysis and several preliminary experiments are conducted. The proposed system has three additional sub-components on the car-door that is, a pair of extra electro-magnetic actuator that are attached to the sliding bar of the open/close car-door four-bar mechanism, a proximity sensor that would be attached to the outside surface of the door which is likely to frequently contact to the object and a driving control circuit of the whole system. A proximity sensor is used to detect object close to the car-door, the driving control circuit provides actuating power command to the electro-magnets to generate braking force to stop the swing motion of the car-door. It is verified through kinematic analysis of the four-bar car-door open/close mechanism and through experiments that the magnitude of maximum electronic magnetic force could provide the braking force enough for this application. For this purpose, an electro-magnet driving circuit is implemented and tested. And also to increase the safety of the system a time delay circuit is implemented and tested.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.212-218
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• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.