• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.

• Information Systems Review
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• v.17 no.3
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• pp.39-64
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• 2015

As information and information technology become more important in competitive corporate environments, the risk of information security breaches has increased accordingly. Although organizations establish security measures to manage information security risks, members of organizations do not comply with them well, and their information security behavior intention is unclear. Therefore, to understand the information security risk management intention of the members of organizations, the present study developed a research model using Protection Motivation Theory, Supervisory Authority Pressure, and Background factors. This study presents empirical research findings based on the analysis of survey data from 201 members of financial institutions. Perceived Severity, Self-efficacy, and Supervisory Authority Pressure had a positive effect on intention; however, Perceived Vulnerability and Response Efficacy did not affect intention. Security Avoidance Habit, which was considered a background factor, had a negative effect on all parameters, and did not have an effect on intention. Security Awareness Training, another background factor, had a positive effect on information security risk management intention and perceived vulnerability, self-efficacy, response efficacy, and supervisory authority pressure, and had no effect on perceived severity. This study used supervisory authority pressure and background factors in the field of information security, and provided a basis to use supervisory authority pressure in future studies on behavior of organizations and members of an organization. In addition, the use of various background factors presented the groundwork for the expansion of protection motivation theory. Furthermore, practitioners can use the study findings as a foundation for organization's security activities, and to improve regulations.

• Korean Journal of Culture and Social Issue
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• v.18 no.3
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• pp.415-433
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• 2012

This study was conducted in order to explain the effect of driving behavior determinants such as drivers' personality and attitude that may induce risky driving behavior and to develop a valid method for discriminating risky drivers using the determinants. In the results of surveying 534 adult drivers, 5 driving behavior determinants (avoidance of problems, benefit/stimulus seeking, interpersonal anxiety, interpersonal anger, and aggression) were found to have a statistically significant effect on drivers' various risky driving behaviors. Using these factors, drivers were grouped according to risk levels (normal drivers, unintentionally risky drivers, and intentionally risky drivers). This result suggests that drivers' dangerous behavior level can be predicted using psychological factors such as their personality and attitude. Accordingly, if the driving behavior determinant model and the base score system used in this study are improved through further research, they are expected to be useful in predicting drivers' recklessness in advance, identifying problems, and providing differentiated safe driving education services based on the results.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.931-940
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• 2012

Social networking services which spreading rapidly is a system using interrelationship of people by internet or mobile. SNS is a network system of the human-centered. In this paper, in order to make robot become a member of social networks we studied the necessary elements and formation. For robot with communication function and sensing, autonomous, collision avoidance method and communication protocol is needed to let Robot share the present conditions dangerous or special situation. We realized this after investigating necessary sensor for SNS, studying robot's collision-avoidance method, and defining protocol of robot for SNS. Also, we suggested and implemented the wired and wireless integrated communications method.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.386-393
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• 2023

Recently, the demand for autonomous navigation technology has increased, and related research is also increasing. Autonomous ships generally follow the planned route, calculate the avoidance route according to the risk situation while sailing, and follow a calculated route. In general, an automatic steering device is used to follow the route, and among the operational automatic steering device methods, the route control mode is the most appropriate method to apply to autonomous ships. Therefore, in this study, we developed a route-tracking algorithm to apply an avoidance route using the navigation control mode of an automatic steering device. The algorithm was developed by dividing the straight and turning sections. A performance test was conducted to satisfy the performance suggested by IEC 62065, the relevant international standard, using simulator equipment that had acquired international certification to verify its performance. The results of the performance verification confirmed that the cross-track error, which represents the straight distance between the ship and the route, satisfied the performance standards suggested by IEC 62065 when the ship followed the route.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.1-7
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• 2021

Detect and avoid (DAA) system, which is essential for the operation of UAS, detects intruding aircraft and offers the ranges of turn and climb/descent maneuver that are required to avoid the intruder. This paper uses detect and avoid alerting logic for unmanned systems (DAIDALUS) developed at NASA as a DAA algorithm. Since DAIDALUS offers ranges of avoidance maneuvers, the actual avoidance maneuver must be decided by the UAS pilot as well as the timing and method of returning to the original route. It can be readily used in real-time human-in-the-loop (HiTL) simulations where a human pilot is making the decision, but a pilot decision model is required in fast-time simulations that proceed without human pilot intervention. This paper proposes a pilot decision model that maneuvers the aircraft based on the DAIDALUS avoidance maneuver range. A series of tests were conducted using test vectors from radio technical commission for aeronautics (RTCA) minimum operational performance standards (MOPS). The alert levels differed by the types of encounters, but loss of well clear (LoWC) was avoided. This model will be useful in fast-time simulation of high-volume traffic involving UAS.

• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.103-108
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• 2008

In the maritime universities, cadets of deck part should practice on board training using training ships of university or merchant vessels of company for 1 year according to STCW Convention. For training period, trainees are educated many education items as to positioning ability, chart work ability, vessel operation ability and cargo operation ability etc. Among many abilities, vessel avoiding ability which is demanded as a basic ability for deck officer can't be gained easily, because avoiding maneuver of ship controlled by cadets is not allowable regally and encounter situations occur randomly. This paper investigated CPA to the various encounter types with other vessels during the ocean going navigation of T.S Hannara. We analysis danger degree per each encounter type, and proposed a basic material of efficient training education about proper look-out and avoiding maneuver.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.293-298
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• 2015

The vessel encounter data collected from the vessel trajectories in the maritime traffic situation is possible to analyze vessel collision and near-collision risk using statistical method. In this study, analyzing variables extracted from the vessel encounter data using factor analysis, we determine main factors effecting vessel collision risk from vessel encounter data. In order to calculate each factor, it used principal component analysis for factor analysis after normalization and standardization of vessel encounter variables. As a result of the factor analysis, main effect factors are summarized into the vessel approach factor and collision avoidance variance factor.

• The Journal of Information Technology
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• v.4 no.2
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• pp.51-68
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• 2001

This study integrates personality trait theory to empirically Investigate the corporate strategy in Korean venture firms. This study predicts that type A/B, locus of control(internal/external), and risk-taking/avoiding will be positively associated with corporate strategy selection. Corporate strategy selection consists of aggressive entry strategy and defensive niche market strategy. Data obtained from a survey of 87 venture business firms is used to construct final variable measures and test the hypothesized relationships. The statistical result shows that type A, internal, and risk-taking CEOs positively associated with aggressive entry strategy, and type B, external, and risk-avoiding CEOs positively associated with defensive niche market strategy. Additional analysis(multiple regression model) to test relatively importance of independents is used.