• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.668-676
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• 2016

The accelerated convergence of automobiles and ICT has led to an increase in in-vehicle electronic devices designed to enhance the safety and convenience of drivers. Consequently, the information presentation on in-vehicle display systems for drivers and passengers need to be taken into account in order to guarantee driving stability while satisfying the needs of UX-based design users. This study compared and evaluated requirements for information items shown on in-vehicle displays regarding driving safety and convenience by groups according to driving career. A total of 38 information items related to safety and convenience that can be displayed while driving and pulling over were collected. Their level of necessity was tested and evaluated by 234 drivers. Using the results, we conducted a comparative analysis on the requirements for information presentation on in-vehicle display systems by groups according to driving career.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.140-147
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• 2012

Vehicle routing problem is one of the traveling salesman problems with various conditions such as vehicle capacity limits, delivery time windows, as well as time dependent speeds in metropolitan area. In this research hourly vehicle moving speeds information in a typical metropolitan area are analyzed to use the results in the design procedure of VRP heuristic. Quality initial vehicle routing solutions can be obtained with adaption of the analysed results of the time periods with no vehicle speed changes. This strategy makes complicated time dependent vehicle speed simple to solve. Time dependent vehicle speeds are too important to ignore to obtain optimum vehicle routing search for real life logistics systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1089-1099
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• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.11-19
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• 2018

In the Unmanned Aerial Vehicle Line-Of-Sight datalink system, there is a possibility that the communication line is disconnected because line of sight can not be secured by one antenna due to changes in position and posture of the air vehicle. In order to prevent this, both top and bottom of air vehicle are equipped with antennas. At this time, if the signal can be transmitted and received by switching to an antenna advantageous for securing the line of sight, communication disconnection can be minimized. The legacy antenna switching method has disadvantages such that diffraction, fading due to the surface or obstacles, interference and reflection of the air vehicle are not considered, or antenna switching standard is not clear. In this paper, we propose an airborne antenna switching method for improving the performance of UAV LOS datalink system. In the antenna switching method, the performance of each of the upper and lower parts of the mounted antenna according to the position and attitude of the air vehicle is predicted by using the deep learning in an UAV LOS datalink system in which only the antenna except the receiver is duplicated. Simulation using flying test dataset shows that it is possible to switch antennas considering the position and attitude of unmanned aerial vehicle in the datalink system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.70-80
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• 2007

Inter-vehicular communication suffers from a variety of the problem on the road, resulting in large delay in propagating emergency warning. An energy depletion as well as a transmission delay may induced by traffic accident. A transmission delay are caused by direct contention from nodes that can hear each other or indirect contention from nodes that can not hear each other, but simultaneously transmit to the same destination. A variety of works have been researched to solve the transmission delay and energy consumption problem in intelligent cars transportation systems. We consider a vehicle-to-vehicle communication protocol for disseminating an emergency information that include end-to-end and energy efficient transmission. In this paper, we propose A vehicle-to-vehicle communication protocol scheme for dissemination emergency information in intelligent cars communication based on IEEE 802.15.3 wireless personal area networks. Results from a simulation study reveal that our scheme can achieves low latency in delivering emergency warnings, and efficiency in consuming energy in stressful road scenarios.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.200-206
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• 2014

This paper describes magnetically levitated vehicle with hybrid magnets, which have been studied by the authors in place of streetcars or conveyance system. An experimental vehicle of 20kg was magnetically levitated by using a small number of dry-cell batteries, which consisted of 10 Ni-MH cells of 1900mAh in series. The magnets were activated sequentially, because the internal resistance of the batteries suppressed the maximum current. The vehicle was kept levitating for about 2 hours and was stable against disturbance due to instantaneous external force. In this paper, dynamic characteristics of the magnetically levitated vehicle using a small number of dry cell batteries are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.719-724
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• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.637-644
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• 2019

In recent years, many public safety systems in the smart city are developed. These systems are taking responsibility to make a safe and comfortable city. In this paper, we propose vehicle tracking systems include a public safety system that enables the policeman to track the stolen vehicles more efficiently by providing the vehicle information in real time. When a vehicle is stolen, the vehicle owner can send a user emergency request. Then, the public safety server which supported by a geospatial query technique will give information such as time, distance, and routes to a policeman who is closest to the location of the vehicle to catch the thief. 300 simulations were performed to evaluate the performance of the system. We found that the average of times required when vehicle owner send a user emergency message on user application until policeman obtain a vehicle tracking request on police application below 1.2 seconds.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.