• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.473-482
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• 2015

Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.11-19
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• 2000

Real-time extraction of traffic information such as the number of vehicles passing, speed, road-occupancy rate, distance between vehicles, and vehicle types from the traffic scenes acquired from the camera on the road, is a core component of the intelligent transportation system(lTS) We present a scheme of extracting the traffic informations based on the spatio-temporal image analysis, which is robust to the variation of weather conditions and the shades. The images of two detection regions for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shade, using the statistical and structural features Quantitative traffic informations are retrieved by analysing the two spatio-temporal images. Since only the local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized while ensuring the detection performance robust to the operating condition.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.584-593
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• 2012

This paper introduces an AVP (Automated Valet Parking) system which applies an autonomous driving concept into the current PAS (Parking Assistant System). The present commercial PAS technology is limited into vehicle. It means vehicle only senses and controls by and for itself to assist the parking. Therefore, the present PAS is restricted to simple parking events. But AVP includes wider parking events and planning because it uses infra-sensor network as well as vehicle sensor. For the realization of AVP, the commercial steering system of a compact vehicle was modified into steer-by-wire structure and various sensors like LRF (Long Range Finder) and camera were installed in a parking area. And local & global server decides where and when the vehicle can go and park in the testing area after recognized the status of environment and vehicle from those sensors. GPS solution was used to validate the AVP performance. More various parking situations, vehicles and obstacles will be considered in the next research stages based on these results. And we expect this AVP solution with more intelligent vehicles can be applied in a big parking lot like a market, an amusement park, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1879-1885
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• 2017

This paper discusses the trajectory tracking system of unmanned ground vehicles based on predictive control. Because the unmanned ground vehicles can not satisfactorily complete the path tracking task, highly efficient and stable trajectory control system is necessary for unmanned ground vehicle to be realized intelligent and practical. According to the characteristics of unmanned vehicle, this paper built the kinematics tracking models firstly. Then studied algorithm solution with the tools of the optimal stability analysis method and proposed a tracking control method based on the model predictive control. The controller used a kinematics-based prediction model to calculate the predictive error. This controller helps the unmanned vehicle drive along the target trajectory quickly and accurately. The designed control strategy has the true robustness, simplicity as well as generality for kinematics model of the unmanned vehicle. Furthermore, the computer Simulink/Carsim results verified the validity of the proposed control method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1933-1954
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• 2013

Multiple wireless devices are being widely deployed in Intelligent Transportation System (ITS) services on the road to establish end-to-end connection between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) networks. Vehicular ad hoc networks (VANETs) play an important role in supporting V2V and V2I communications (also called V2X communications) in a variety of urban environments with distinct topological characteristics. In fact, obstacles such as big buildings, moving vehicles, trees, advertisement boards, traffic lights, etc. may block the radio signals in V2X communications. Their impact has been neglected in VANET research. In this paper, we present a realistic and efficient radio propagation model to handle different sizes of static and moving obstacles for V2X communications. In the proposed model, buildings and large moving vehicles are modeled as static and moving obstacles, and taken into account their impact on the packet reception rate, Line-of-sight (LOS) obstruction, and received signal power. We use unsymmetrical city map which has many dead-end roads and open faces. Each dead-end road and open faces are joined to the nearest edge making a polygon to model realistic obstacles. The simulation results of proposed model demonstrates better performance compared to some existing models, that shows proposed model can reflect more realistic simulation environments.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1B
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• pp.1-8
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• 2012

In this paper, we propose an algorithm to improve collision avoidance in Vehicle-to-Vehicle (V2V) networks based on IEEE 802.11p. Since IEEE 802.11p adopts CSMA/CA as a multiple access scheme and an emergency warning message (EWM) is delivered to behind vehicles in a multi-hop manner, due to transmission collision, the more vehicles in the vehicle chain results in a longer delay. The longer delay increases the possibility of a rear-end collision. In order to ensure message reception with low latency, we consider implicit acknowledgement of a broadcasted EWM message and propose an algorithm to reduce redundant message transactions, called Two-Way Implicit Acknowledgement (TWIA). By simulations, we show that our proposed algorithm can reduce the latency until the last car receives the message by 9% and the success rate every car receives the message within 0.7sec by 12% at 100 fixed-number-of-car environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.81-86
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• 2020

With the development of the intelligent Internet of Things AIoT that goes beyond the IoT of the Internet of Things, the industry is changing overall. In addition, with the advent of the 4th Industrial Revolution, revolutionary changes and developments are also taking place in the automobile industry. A representative example is "autonomous driving vehicle". Because the domestic and foreign interests in autonomous vehicles have increased, many developments have been made, and although limited, they have developed into the commercialization stage. However, the structure of the autonomous vehicle that collects, analyzes, and controls data using various sensors installed in the vehicle, not the driver, is often insufficiently exposed to hacking due to the lack of multiplexed devices for security. In this case, as this can be a threat not only to the driver, but also to the surrounding environment, this paper proposes a new data processing function to improve the system security of autonomous vehicles.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.91-97
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• 2002

This paper describes a heuristic search technique carrying out collision avoidance for Autonomous Underwater Vehicles(AUVs). Fuzzy relational products are used as the mathematical implement for the analysis and synthesis of relations between obstacles that are met in the navigation environment and available candidate nodes. In this paper, we propose a more effective evaluation function that reflects the heuristic information of domain experts on obstacle clearance, and an advanced heuristic search method performing collision avoidance for AUVs. The search technique adopts fuzzy relational products to conduct path-planning of intelligent navigation system. In order to verify the performance of proposed heuristic search, it is compared with $A^*$ search method through simulation in view of the CPU time, the optimization of path and the amount of memory usage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.632-637
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• 2019

Recent researches on autonomous driving of vehicles are becoming very active, and it is a trend to assist safe driving and improve driver's convenience. Autonomous vehicles are required to combine artificial intelligence, image recognition capability, and Internet communication between objects. Because mobile telecommunication networks have limitations in their processing, they can be easily implemented and scale using an easily expandable Wi-Fi network. We propose a wireless design method to construct such a vehicle control network. We propose the arrangement of AP and the software configuration method to minimize loss of data transmission / reception of mobile terminal. Through the design of the proposed network system, the communication performance of the moving vehicle can be dramatically increased. We also verify the packet structure of GPS, video, voice, and data communication that can be used for the vehicle through experiments on the movement of various terminal devices. This wireless design technology can be extended to various general purpose wireless networks such as 2.4GHz, 5GHz and 10GHz Wi-Fi. It is also possible to link wireless intelligent road network with autonomous driving.