• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.472-477
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• 2018

In this paper, we develop interactive content services for preventing depression of users through an intelligent Internet of Things(IoT) mirror system. For interactive content services, an IoT mirror device measures attention and meditation data from an EEG headset device and also measures facial expression data such as "sad", "angery", "disgust", "neutral", " happy", and "surprise" classified by a multi-layer perceptron algorithm through an webcam. Then, it sends the measured data to an oneM2M-compliant IoT server. Based on the collected data in the IoT server, a machine learning model is built to classify three levels of depression (RED, YELLOW, and GREEN) given by a proposed merge labeling method. It was verified that the k-nearest neighbor (k-NN) model could achieve about 93% of accuracy by experimental results. In addition, according to the classified level, a social network service agent sent a corresponding alert message to the family, friends and social workers. Thus, we were able to provide an interactive content service between users and caregivers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.15-27
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• 2017

In general, increasing train dwell time leads to increasing train service frequency, and it in turn contributes to increasing the congestion level of train and platform. Therefore, the studies on train dwell time have received growing attention in the perspective of scheduling train operation. This study develops a prediction model of train dwell time to enable train operators to mitigate platform congestion by metering passenger inflow at platform gate with respect to platform congestion levels in real-time. To estimate the prediction model, three types of independent variables were applied: number of passengers to get into train, number of passengers to get out of trains, and train weights, which are collectable in real-time. The explanatory power of the estimated model was 0.809, and all of the dependent variables were statistically significant at the 99%. As a result, this model can be available for the basis of on-time train service through platform gate metering, which is a strategy to manage passenger inflow at the platform.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.12-25
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• 2009

The purpose of this study is to identify and analyze drivers' attitude related to usage of traffic information and traffic management service. A sample survey on Seohaeanseon Expressway(15), Gyeongbu Experssway(1), Youngdong Expressway(50) was conducted to analyze drivers' attitude ; sample size is 304 with 95% of confidence level and ${\pm}3.6%$ of sampling error. The analysis lists of drivers' attitude are usage of traffic information, awareness about information dissemination devices, and awareness about traffic control information related to LCS or RWIS. The results of this study is that drivers want pre-trip information, voice-based Hi-pass OBU, and fast incident management. According to the IPA, KEC's main consideration is a traffic flow improvement.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.681-690
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• 2001

In this paper, we propose a steering concept that considers overall aspects in the CBSD (Component-Based Software Development) environments. While many researches which are concentrated on using components, market promotion and component development itself seem to be insufficient. To overcome this problem, we introduce a brokerage concept called“Value-Added Brokerage Concept”that provides the following three services：1) domain architecture-based component promotion, 2) intelligent component search, and 3) white-box service. Domain architecture-based component promotion facilitates balancing component production and promoting architecture-level large scale reuse. Intelligent component search enables to overcome the long time search and selection problem. Finally, white-box service is for solving maintenance problems, which is one of the most critical problem in the CBSD environments. Especially, we expect this proposed concept would be well adapted to our national environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.132-145
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• 2021

This study analyzes the main road network for road users to manage roads efficiently and derives problematic road sections to be improved. Traditional road management has been operated by manager-oriented view and a diversified road management system based on congestion. Therefore, in this research, the mail road Network was selected from the viewpoint of passenger-oriented, logistics-oriented and tourism-oriented, and the problematic road sections were derived through Level Of Service (LOS) analysis, safety analysis using EPDO accident rate, and network service analysis. This study emphasizes the efficient user-oriented road construction and management system and the need of constructing a mail road network, and it suggests the improvement strategies.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.390-399
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• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.266-283
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• 2022

With the rapid development of autonomous vehicle technology, unexpected accidents are occurring. Therefore, it is necessary to minimize user accident damage through the development of autonomous traffic safety education. Since edge cases, accident type, and risk factor analysis are important for realistic education, overseas case studies and demonstrations were carried out, and based on this, two curriculum for service providers and general users were developed. The service provider curriculum consisted of OEDR, sudden stop, cut-in, take-over, defensive driving, system malfunction, policy and information security education, and the general user curriculum consisted of attention duty, take-over, operating design domain, accidents type, laws, functions, information security education.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.55-63
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• 2023

In this paper, we propose a function and service of the Disaster Crisis Alert Management System that automatically analyzes the situation judgment criteria to issue a disaster crisis alert and a plan to operate in the National Disaster Management System(NDMS). In the event of a disaster, a crisis alert(interest-caution-alert-serious) is issued according to the crisis alert level. In order to automatically analyze and determine the crisis alert level, first, data collection, crisis alert level analysis, crisis alert level judgment, and disaster crisis alert management system that expresses the crisis alert level by spatial scale(province, city, district) were implemented. The crisis alert level was analyzed and expressed in two ways by applying the intelligent crisis alert level(determination of regional sensitivity, risk level, and crisis alert level) and the crisis alert standard of the crisis management manual(province-level standard setting). Second, standard metadata, linkage of situation information of target) and API standards for data provision are presented to jointly utilize data linkage and crisis alert data of the disaster and safety data sharing platform so that it can be operated within the NDMS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.22-34
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• 2011

This paper presents the investigation results of a research on how engineers can analyze the economic effect of the ETCS(Electronic Toll Collection System) installed to minimize the vehicle delays on freeway tollgates during toll payments. This research considered this economic effect to occur in the form of vehicle passing time reductions at the ETCS, and the multi-service queuing theory was applied to estimate these values. This research found: 1) When vehicles approaching tollgates show Poisson distribution and the service time of the ETCS shows Exponential distribution, the multi-service queuing theory would be applicable for estimating vehicle passing times at toll-gates, 2) Despite the ETCS placement, exit sections of tollgates give a greater reduction of vehicle passing times than entering sections due to more delays at conventional toll payments, and 3)The ETCS would not guarantee vehicle passing time reductions all the time, because in such a case as many vehicles were queuing at the ETCS, the total delay level for a toll gate would increase greatly. In addition, in order to examine the accuracy of the estimated vehicle passing values, this research compared the values from the multi-service queuing theory with the observed values from a set of field survey values at freeway toll-gates, and found that the two values were in a good agreement with a very low error range of 1-3 seconds per vehicle. Based on this result, the multi-service queuing theory was recommended for practice.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.103-116
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• 2022

The South Korean Ministry of Land, Infrastructure, and Transport designated seven automated driving test beds required to evaluate vehicle performance every year for the expansion of mobility services based on automated driving. As a fundamental study, we suggested a necessary example of evaluating the performance with a satisfaction survey for the services before the evaluation. First, we surveyed the perception of automated driving services of users and the public in Sejong-si, South Korea. The survey showed that the users had a higher level of awareness of automated driving technology and intention to use it than the public. Second, the satisfaction survey was conducted on demand-responsive public transportation and automated driving service users. Notably, using the Wilcoxon Rank Sum Test, among the non-parametric statistical analysis methods, we found that safety-related factors affected the overall satisfaction of users of automated driving services. On the other hand, in the case of the demand-responsive public transportation service users, factors related to service convenience affected overall satisfaction. Hence, the results of these surveys are expected to be used as basic data and guidelines to improve the quality of automated driving services and policy establishment.