• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.15-30
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• 2019

The reduction of traffic accidents is a primary potential benefit of autonomous vehicles (AVs). However, the prevalence of AVs also arouses a key question: to what extent should a human wrest control back from AVs? Specifically, in an unavoidable situation of emergency, should an AV be able to decide between the safety of its own passengers and endangered pedestrians? Should AV programming include well-accepted decision rules about actionsto take in hypothetical situations? The current study (N = 103) examined individual/situational variables that could perform critical decision-making roles in AV related traffic accidents. The individual variable of attitudes toward AVs was assessed using the Self-driving Car Acceptance Scale. To investigate situational influences on decisional processes, the study's participants were assigned to one of two groups: the achievement value was activated in one group and the benevolence value was triggered in the other through the use of a sentence completion task. Thereafter, participants were required to indicate who should be protected from injury: the passengers of the concerned AV, or endangered pedestrians. Participants were also asked to record the extent to which they intended to buy an AV programmed to decide in favor of the greater good according to Utilitarian principles. The results suggested that participants in the "achievement value: driver perspective" groupexpressed the lowest willingness to sacrifice themselves to save several pedestrians in an unavoidable traffic accident. This group of participants was also the most reluctant to buy an AV programmed with utilitarian rules, even though there were significant positive relationships between members' acceptance of AVs and their expressed intention to purchase one. These findings highlight the role of the decisional processes involved in the "achievement value" pertaining to AVs. The paper finally records the limitations of the present study and suggests directions for future research.

• Journal of Korean Academy of Nursing
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• v.18 no.1
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• pp.19-25
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• 1988

To ensure the autonomy of nursing care aetivies is one of the major and most interesting issues in the field of nursing. The pertaining autonomy demands the nurse to make decisions of her or his own with out interference and free of help from other sides of health care agency. The whole process of autonomous nursing behavior should be judged and conveyed by the nurse only on the basis of the internal factors of her care to solve the problems of the client's disorder in health. Truth of nursing science and relevence of nursing conduct depend on our construction of internal basis and establishment of self-sufficient reference system. The information for efficient decision-making at the scene of nursing can only be supplied by a systematic body of nursing science consisting of true or properly corroborated propositions. The science of nursing can be autonomous when we have framework of explanation, independently of other sciences and the behavior of nursing care can factually be independent of and peculiar to that of other but similar fields only when the science of nursing is correspondently autonomous.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.522-531
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• 2001

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.635-641
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• 2008

In this paper, we used a laser range finder (LRF) to detect both the static and dynamic obstacles for the safe navigation of a mobile robot. LRF sensor measurements containing the information of obstacle's geometry are first processed to extract the characteristic points of the obstacle in the sensor field of view. Then the dynamic states of the characteristic points are approximated using kinematic model, which are tracked by associating the measurements with Probability Data Association Filter. Finally, the collision avoidance algorithm is developed by using fuzzy decision making algorithm depending on the states of the obstacles tracked by the proposed obstacle tracking algorithm. The performance of the proposed algorithm is evaluated through experiments with the experimental mobile robot.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.439-449
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• 2020

This study aimed to identify factors influencing the preferences for end-of-life (EOL) care among undergraduate nursing students. In this cross-sectional study, data were collected from December 2017 to February 2018. This study included 217 undergraduate nursing students. Factors influencing the preference for 'autonomous physiological decision-making' were the following: education level(by grade), having biomedical education, attitude towards death, and attitude towards life-sustaining treatments (LSTs). Preference for 'decision-making by healthcare professionals' was related to having a religion. Factors influencing the preference for 'spirituality' were education level, having a religion, and academic major satisfaction. Preference for 'pain control' was associated with education level, experience with dying patients, bad self-rated health, attitude towards death, and attitude towards LSTs. The study findings suggest that education regarding LSTs, EOL care, and EOL decision-making in nursing curricula is essential.

• Convergence Security Journal
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• v.18 no.2
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• pp.101-111
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• 2018

The autonomous weapon systems are being developed with a global competition due to the 4th industrial revolution technologies such as artificial intelligence. This theses analyzes on the technologies related to the autonomy of the new weapons, the new changes in war fighting regime that will be brought by such autonomous weapons, the level of autonomy in a autonomous weapon system, and also the definition and functions of the autonomy. The advanced artificial intelligence for the civilian commercial sectors would be similar to the required military autonomous systems. The future war fighting regime would be the war with autonomous weapon systems without any human casualties. The level of autonomy in the future weapons would be fully autonomous without any human supervision or involvement in the decision making processes. The functions of the autonomous weapon would be to sense, to decide, and to act with a full autonomy in order to accomplish desired purposes.

• Annual Conference of KIPS
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• 2004.05a
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• pp.365-368
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• 2004

본 논문에서는 상태변화에 대한 자율적 의사결정을 하는 퍼지논리를 이용한 에이전트를 구현하는 것을 연구의 목적으로 한다. 이를 위하여 제한적인 조건을 설정하여 부분적인 실험을 하였다. 에이전트를 구성하기 위한 추론방식으로는 max-product 기법을 사용하였으며, n개 퍼지 규칙들 또는 연관들 $(A_1,\;B_1),\;{\ldots},\;(A_n,\;B_n)$을 가지는 상황을 고려하여 비퍼지화 작업을 수행하여 중심값을 추출하여 추론 작업을 실행하였다.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.458-470
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• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.400-400
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• 2000

This paper purposed that verify the validity of Petri Net method for control progressive increase of system complexity, before extend the realized single robot system to multi-robot system. An autonomous mobile robot(AMR) needs decision making, motion control, path planning, tracking a path, obstacle avoidance, and sensor fusion, to complete its task. An AMR integrates and operates these technics through a consistent command system. An error in a command hierarchy which is like duplication or omission of a control command hierarchy for each module results in serious problems. This paper minimizes the error by modeling each module and whole system using Petri Net graphical representation and applies it to the exploration task of an AMR