• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.106-112
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• 2012

Smart Highway is the intelligent highway that improves a traffic safety, reduces incidence of traffic accidents, and supports intelligent and convenient driving environment so that drivers can drive at high speeds in safety[1]. In order to implement the highway, it is required to gather a dangerous data such as obstacle, wild animal, disabled car, etc. To provide the situation information of the highway, it has been gathered traffic information using various sensors. However, this technique has problems such as the problems of various information gathering, lack of accuracy depending on weather conditions and limitation of maintenance. Therefore, in order to provide safe driving information to driver by gathering dangerous condition, radar system is needed. In this paper, we used a developing 34.5GHz RWR(Road Watch Radar) radar for gathering dangerous information and we verified performance of obstacle detecting and resolution through field test.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.213-222
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• 2018

This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.1-15
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• 2022

In order to trust and use autonomous vehicles, safe driving on the road must be guaranteed. For this, the first infrastructure to be equipped with autonomous driving is traffic safety facility. On the other hand, autonomous vehicles(Level 3) and general vehicles are driving on the road, it is necessary to additionally manage existing general traffic safety facilities. In this study, a field management system for traffic safety facilities based on autonomous driving infrastructure was studied, and a pilot field management system was implemented in the demonstration area(Pangyo). The pilot system consists of a GNSS(Global Navigation Satellite System) receiver, a field management equipment, and a field management app. As a result of field demonstration,, it was confirmed that traffic safety facility information was easily transmitted and received even in downtown areas and that could be efficiently operated and managed. It is expected that the results of this study will be used as reference materials for the spread of autonomous driving infrastructure to local governments and infrastructure construction in the future.

• Convergence Security Journal
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• v.19 no.3
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• pp.71-79
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• 2019

The demand of smart cars is increasing rapidly. International stand organize such as 3GPP and 5GAA are proposing standard communication protocvols for connected-car, and automotive network infrastructure. But Smart car network have many security threats and more dangerous against the existed wire communication network. Typically, peripheral devices of a smart car may disguise their identity and steal location information and personal information about the vehicle. In addition, the infrastructure elements around smart cars can conspire and put driving cars in danger, threatening lives. This is a very serious security threat. Therefore, in order to solve these problems, we proposed a system that is secure from collusion and tampering attacks using attribute-based authorize delegation method and threshold encryption algorithms. We have demonstrated using a semantic safety model that the proposed system can be safe from collusion attack.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.16-24
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• 2012

This paper proposes a method utilizing Differential Global Position System (DGPS) with Real-Time Kinematic (RTK) and pre-built Geo-graphic Information System (GIS) to detect lane departure of a vehicle. The position of a vehicle measured by DGPS with RTK has 18 cm-level accuracy. The preconditioned GIS data giving accurate position information of the traffic lanes is used to set up coordinate system and to enable fast calculation of the relative position of the vehicle within the traffic lanes. This relative position can be used for safe driving by preventing the vehicle from departing lane carelessly. The proposed system can be a key component in functions such as vehicle guidance, driver alert and assistance, and the smart highway that eventually enables autonomous driving supporting system. Experimental results show the ability of the system to meet the accuracy and robustness to detect lane departure of a vehicle at high speed.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.34-46
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• 2021

In order to accelerate the commercialization of self-driving cars, it is necessary to accurately identify the causes of deteriorating the driving safety of the current self-driving cars and try to improve them. This study conducted a questionnaire survey of experts studying autonomous driving in Korea to identify the causes of problems in the driving safety of autonomous vehicles and the level of autonomous driving technology in Korea. As a result of the survey, the construction section, heavy rain/heavy snow conditions, fine dust conditions, and the presence of potholes were less satisfied with the current technology level than their importance, and thus priority research and development was required. Among them, the failure of road/road facilities and the performance of the sensor itself in the construction section and the porthole, and the performance of the sensor and the absence of an algorithm were the most responsible for the situation connected to the weather. In order to realize safe autonomous driving as soon as possible, it is necessary to continuously identify and resolve the causes that hinder the driving safety of autonomous vehicles.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.11-16
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• 2023

Vehicular networks are part of the next generation wireless and smart Intelligent Transportation Systems (ITS). In the future, autonomous vehicles will be an integral part of ITS and will provide safe and reliable traveling features to the users. The reliability and security of data transmission in vehicular networks has been a challenging task. To manage data transmission in vehicular networks, road networks are divided into clusters and a cluster head is selected to handle the data. The selection of cluster heads is a challenge as vehicles are mobile and their connectivity is dynamically changing. In this paper, a novel secure cluster head selection algorithm is proposed for secure and reliable data sharing. The idea is to use the secrecy rate of each vehicle in the cluster and adaptively select the most secure vehicle as the cluster head. Simulation results show that the proposed scheme improves the reliability and security of the transmission significantly.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.403-408
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• 2023

In this paper, we introduce the results of the development of a care robot for the safe lifting and transportation of bedridden patients with difficulty moving by themselves, especially, in medical facilities. The purpose of the developed patient transfer robot is to improve the convenience of care givers and enhance the safety and comfort of care recipients by facilitating patient lifting and patient transfer tasks by applying robot technology. In order to implement the lifting function, a hoist was designed and developed, and a sway control and rollover warning system were included in the hoist module as product differentiators. In addition, in terms of implementing the transfer function, an omnidirectional movement mechanism to improve operability in confined spaces and an active safety system to prevent collisions were developed. The function of the developed patient transfer robot was verified through performance evaluation by an authorized testing agency.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.136-142
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• 2014

Distinct features in heart rate signals during the driver's wake and sleep states could provide an initiative for the development of a safe driving systems such as drowsiness detecting sensor in a smart wheel. We measured ECG from health subjects ($23.5{\pm}2.5$ in age) during the wake and drowsiness states. The proposed method is able to detect R waves and R-R interval calculation in the ECG even when the signal includes in abnormal signals. Heart rate variability(HRV) was investigated for the time domain and frequency domains. The STD HR(0.029), NN50(0.044) and VLF power(0.0018) of the RR interval series of the subjects were significantly different from those of the control group (p < 0.05). In conclusion, there are changes in heart rate from wake to drowsiness that are potentially to be detected. The results in our study could be useful for the development of drowsiness detection sensors for effective real-time monitoring.