• Journal of Navigation and Port Research
• /
• v.32 no.2
• /
• pp.127-132
• /
• 2008

The safety degree of navigation for collision avoidance is closely related with the combination between mariner's behavior and navigational environment. The condition of navigational environment is mainly decided by navigable waters, ship traffic, rule of road, sea state, weather and so on. Especially, the condition of navigable waters and ship traffic in navigational environment are ones of the important factors to attain safe navigation when mariners are underway and crossing, head on or overtaking situation. Thus this paper is to analyze the characteristics of mariner's behavior for collision avoidance caused by ship traffic and navigable waters by analyzing the contents of questionnaire and the results of international collaborative research. As a result, it can be concluded that the density of ship traffic and the area of navigable waters affect mariner's ship handling for collision avoidance.

• International Journal of Aeronautical and Space Sciences
• /
• v.6 no.2
• /
• pp.97-109
• /
• 2005

In this paper, the critical requirement for obstacle awareness and avoidance is assessed with the compliance of the equivalent level of safety regulation, and then the collision avoidance sensor system is presented with the key design parameters for the requirement of the smart unmanned aerial vehicle in low-altitude flight. Based on the assessment of various sensors, small-sized radar sensor is selected for the suitable candidate due to the real-time range and range-rate acquisition capability of the stationary and moving aircraft even under all-weather environments. Through the performance analysis for the system requirement, the conceptual design result of radar sensor model is proposed with the range detection probability and collision avoidance mode is established based on the time-to-collision, which is analyzed by collision scenario.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2003.11a
• /
• pp.203-207
• /
• 2003

Due to the inherent nature of the low flying UAV, obstacle detection is a fundamental requirement in the flight path to avoid the collision from obstacles as well as manned aircraft. In this paper, a preliminary sensor requirements of an obstacle detection system for UAV in low-altitude flight are analyzed, and the automated obstacle detection sensor system is proposed assessing both passive and active sensors such as EO camera, IR, Laser radar, microwave and millimeter radar. In addition, TCAS (Traffic Alert and Collision Avoidance System) are reviewed for the collision avoidance of the manned aircraft system. It is suggested that small-sized radar sensor is the best candidate for the smart UAV because an active radar can provide the real-time informations on range and range rate in the all-weather environment. However, an important constraints on small UAV should be resolved in terms of accommodation of the mass, volume, and power allocated in the payload of the UAV system design requirements.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.2
• /
• pp.91-99
• /
• 2024

Collision avoidance system is important to improve the robustness and functional safety of autonomous vehicles. This paper proposes an object-level distance estimation method to develop a collision avoidance system, and it is applied to golfcarts utilized in country club environments. To improve the detection accuracy, we continually trained an object detection model based on pseudo labels generated by a pre-trained detector. Moreover, we propose object-aware depth estimation (OADE) method which trains a depth model focusing on object regions. In the OADE algorithm, we generated dense depth information for object regions by utilizing detection results and sparse LiDAR points, and it is referred to as object-aware LiDAR projection (OALP). By using the OALP maps, a depth estimation model was trained by backpropagating more gradients of the loss on object regions. Experiments were conducted on our custom dataset, which was collected for the travel distance of 22 km on 54 holes in three country clubs under various weather conditions. The precision and recall rate were respectively improved from 70.5% and 49.1% to 95.3% and 92.1% after the continual learning with pseudo labels. Moreover, the OADE algorithm reduces the absolute relative error from 4.76% to 4.27% for estimating distances to obstacles.

• Journal of electromagnetic engineering and science
• /
• v.7 no.3
• /
• pp.129-133
• /
• 2007

In this paper, we present the development of an antenna specialized for the maritime collision avoidance system. This antenna is configured as the dielectric rod partially embedded in the metal cavity to reduce the overall size, simultaneously assuring the mechanical sturdiness against the challenging oceanic weather conditions. More importantly, the design has been carefully done to meet the requirements on the radiation pattern(with the slope < 5 dB/deg in the elevation(E-plane), circular in the azimuth) suitable to receiving the reflected signals from the other objects on the sea. To find the optimal design parameters, the genetic algorithm has been used to meet the goals of the desired return loss and pattern. This design methodology is validated by the good agreement between the calculation and measurement.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.4
• /
• pp.361-367
• /
• 2010

This paper reports the development of a mobile robot for patrol using a single laser range finder. A Laser range finder is useful for outdoor environment regardless of illumination change or various weather conditions. In this paper we combined the motion control of the mobile robot and the algorithm for detecting the outdoor environment. For obstacle avoidance, we adopted the Vector Field Histogram algorithm. A laser range finder is mounted on the mobile robot and looking down the road with a small tilt angle. We propose an algorithm for detecting the surface of the road. The outdoor patrol robot platform is equipped with a DGPS system, a gyro-compass sensor, and a laser range finder. The proposed obstacle avoidance and road detection algorithms were experimentally tested in success.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.6 no.4
• /
• pp.1014-1023
• /
• 2014

In this paper the real life operation of ULCS (Ultra Large Container Ships) is presented from the point of view of shipmasters. The paper provides interpretation of results of questionnaire filled by masters of large container ships during Tools for Ultra Large Container Ships (TULC) EUI FP7 project. This is done in a way that results of questionnaire are further reviewed and commented by experienced master of ULCS. Following phenomena are subject of questionnaire and further discussed in the paper: parametric rolling, slamming, whipping, springing, green water and rogue waves. Special attention is given to the definition of rough sea states as well as to measures that ship masters take to avoid them as well as to the manoeuvring in heavy seas. The role of the wave forecast and weather routing software is also discussed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.3
• /
• pp.290-295
• /
• 2011

On the basis of DCPA(Distance to Closest Point of Approach) and TCPA(Time to CPA), the conventional algorithms for collision avoidances have a drawback that the '72 CORLEGs(International Regulations for Preventing Collisions at Sea, 1972) has not taken into account to prevent collisions between ships. In this paper, the proposed algorithm decides whether the own ship is a give-way vessel or a stand-on vessel by observing the relative bearing of the encountered ship. To determine the ship position and time for collision avoidance, the proposed algorithm utilizes the ellipse model for ship safety domain. The computer simulation is done to represent the process of adversive behavior. Using the proposed method, the past maritime accident is analyzed. The proposed method can be effectively applied to collision avoidance by CORLEGs even when the target ship's navigational lights is invisible in poor weather and/or in the restricted visibility.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.75-84
• /
• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of Advanced Navigation Technology
• /
• v.27 no.1
• /
• pp.36-42
• /
• 2023

The development of autonomous vehicles are currently being actively carried out by various companies and research institutes. Expectations for commercialization in daily life as well as specific industries are also rising. Simulators for autonomous vehicles are an essential element in algorithm development and execution considering stability and cost. In this need, various simulators and platforms for simulators are emerging, but research on simulations that reflect various meteorological environmental factors in the real world is still insufficient. This paper proposes a traffic simulation for autonomous vehicles that can consider the weather environment. The weather environment that can be set is largely classified into four categories, and an improved collision prevention algorithm to apply them is presented. Simulation development was conducted through Carla's Python API, a development tool for autonomous driving, and the performance results were compared with existing collision algorithms. Through this, we tried to propose improvements for the development of advanced self-driving vehicle simulations that can reflect various weather environmental factors in real life.