• 한국콘텐츠학회논문지
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• 제20권5호
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• pp.281-290
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• 2020

모바일광고 회피행동에 영향을 미치는 요인들 간 관계를 살펴보기 위해 소비자가 느끼는 광고 오락성, 정보성, 관련성, 신뢰성, 지각된 침입성이 광고회피에 어떠한 영향을 미치는지 살펴보고자 하였다. 또한 이러한 광고 특성이 광고회피에 미치는 영향에서 국가 및 연령에 따라 차이가 있는지 살펴보고자 하였다. 본 연구는 20대와 40대의 한국과 중국의 일반인 254명을 대상으로 모바일광고에 대한 회피를 조사하고 그 결과를 비교분석의 관점에서 평가하였다. 수집된 자료는 다중회귀분석과 위계적 회귀분석을 통해 검증하였다. 광고 오락성, 관련성이 높을수록 광고회피가 감소하는 결과가 나타났으며, 지각된 침입성이 높을수록 광고회피가 증가하는 결과가 나타났다. 또한 광고 오락성, 정보성, 관련성, 신뢰성이 광고회피에 미치는 영향에서 국가 및 연령별 차이가 있었으나, 지각된 침입성이 광고회피에 미치는 영향에서 국가 및 연령별 유의한 차이가 나타나지 않았다. 연구 결과를 토대로 광고회피를 유발하는 예측 요인이 무엇인지 국가 및 연령별로 비교하여 파악함으로써 소비자의 모바일 광고회피를 줄이는 방안을 모색하고자 하였다는 측면에서 연구의 시사점을 들 수 있다.

• 한국자동차공학회논문집
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• 제7권8호
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• pp.233-247
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• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.

• 한국항공운항학회지
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• 제30권2호
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• pp.34-43
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• 2022

In Efforts to prevent CFIT accidents so far, have been emphasizing various education measures to minimize the occurrence of human errors, as well as enforcement measures. However, current engineering measures remain in a system (TAWS) that gives warnings before colliding with ground or obstacles, and even actual automatic avoidance maneuvers are not implemented, which has limitations that cannot prevent accidents caused by human error. Currently, various attempts are being made to apply machine learning-based artificial intelligence agent technologies to the aviation safety field. In this paper, we propose a deep reinforcement learning-based artificial intelligence agent that can recognize CFIT situations and control aircraft to avoid them in the simulation environment. It also describes the composition of the learning environment, process, and results, and finally the experimental results using the learned agent. In the future, if the results of this study are expanded to learn the horizontal and vertical terrain radar detection information and camera image information of radar in addition to the terrain database, it is expected that it will become an agent capable of performing more robust CFIT autonomous avoidance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.266-268
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• 2005

Recently, the ability of sensing obstacles by oneself and creating suitable moving path in mobile robots are required to provide various kinds automation services. Therefore, in this paper, we studied the avoidance behavior of mobile robots from dynamic obstacles using potential function that minimizes distance and time. We examined the performance of the proposed algorithm by comparing the method of based on the geometrical experience in simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.643-648
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• 1989

This paper presents a theoretic study and computer simulation of models and approaches for dynamical obstacle avoidance by mobile robots. The movement of obstacles in unknown environment is described by any one or a combination of three models. The control strategy of the mobile robots is formulated based on one of three approaches. A trajectory-guided control strategy for dynamical obstacle avoidance has been developed. The method greatly simplifies the control process of mobile robots, and is computationally attractive.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1689-1693
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• 2003

Communication based train control system is applied regularly worldwide. And this system may be used in domestic soon. Communication based train control system does not depend on conventional track circuit. Therefore, position and distance control of train to prevent collision with leading train may become important safety factor. This paper developed collision avoidance algorithm to control trains of several units efficiently for this. In developing a collision avoidance algorithm, it is desirable to avoid the need for additional system. Additional system restricts the development of the algorithm by limiting the effectiveness of the algorithm to only those areas where the additional system can be afforded and has been installed.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권9호
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• pp.402-412
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• 2002

The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.7-12
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• 1992

This paper proposes a sensor-based path planning method which utilizes fuzzy logic and neural network for obstacle avoidance of a mobile robot in uncertain environments. In order to acquire the information about the environment around the mobile robot, the ultrasonic sensors mounted on the front of mobile robot are used. The neural network, whose inputs are preprocessed by ultrasonic sensor readings, informs the mobile robot of the situation of environment in which mobile robot is at the present instant. Then, according to the situation class, the fuzzy rules are fired to make a decision on the mobile robot action. In addition, this method can be implemented real time since the number of fuzzy rules used to avoid the obstacle is small. Fuzzy rules are constructed based on the human reasoning and tuned by iterative simulations. The effective of the proposed avoidance method is verified by a series of simulations.

• 로봇학회논문지
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• 제13권2호
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• pp.121-128
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• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권3호
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• pp.245-249
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• 2012

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process.