• 한국지능시스템학회논문지
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• 제21권3호
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• pp.323-328
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• 2011

실제 시스템 적용에 있어서, 수중비행체(Underwater Flight Vehicle : UFV)의 자율제어(autonomous control)를 위한 3-D 장애물회피(obstacle avoidance) 시스템은 다음과 같은 문제점들을 가지고 있다. 즉, 소나(sonar)는 지역적 탐색영역 내에서 장애물의 거리(range)/방위(bearing) 정보를 제공하며, 자율수중운동체(Autonomous Underwater Vehicle : AUV) 관점에서 에너지 소비 및 음향학적 소음이 적은 시스템을 필요로 하며, 최대 피치 및 심도와 같은 UFV 운용 제약조건을 가진다. 나아가, 구조와 파라메터의 관점에 있어서 용이한 설계 절차를 요구한다. 이 문제를 해결하기 위해서 진화 전략(Evolution Strategy : ES) 및 퍼지논리 제어기(Fuzzy Logic Controller : FLC)를 이용하는 지능형 3-D 장애물회피 알고리즘이 제안되었다. 제안된 알고리즘의 성능을 검증하기 위해 UFV의 3-D 장애물회피가 수행되었다. 시뮬레이션 결과는 제안된 알고리즘이 실제 시스템에 존재하는 문제점들을 효과적으로 해결하고 있음을 보여준다.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.63-71
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• 2013

WAVE(Wireless Access for Vehicular Environment) System is a communication technology to monitor system failure and vehicle functions and management services to prevent possible incidents of driving a vehicle. In this paper, we have designed and implemented the mutual message processing through parameter between WME management module that manages WAVE system and MLME that manages the upper layer MAC(Media Access Control) module. Also, in order to verify the validity, we have carried out experiments to compare the speed of data processing by dividing data of 1Mbyte, 2Mbyte, 3Mbyte into the packets of 2KByte and 4KByte. Experiments data processing speed of 2KByte packet were shown about 173.62ms in 1MByte, 2MByte about 352.61ms, 3MByte about 550.13ms and, data processing speed of 4KByte packet, 1MByte approximately 87.56ms, 2MByte about 177.94ms, 3MByte about 277.18ms. Therefore, in WAVE system, the mutual messages processing through the parameters between WME and MLME module can be utilized in the various service of ITS(Intelligent Transportation Systems) depending on the speed of data processing.

• 한국정보시스템학회지:정보시스템연구
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• 제29권2호
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• 한국자동차공학회논문집
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• 제20권4호
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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.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.635-640
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• 2009

실제 시스템 적용에 있어서, 수중비행체(Underwater Flight Vehicle : UFV)의 자율제어(autonomous control)를 위한 장애물회피(obstacle avoidance) 시스템은 다음과 같은 문제점들을 가지고 있다. 즉, 소나(sonar)는 지역적 탐색영역 내의 장애물 정보만을 제공할 수 있으므로 지역적 정보를 가지며, 에너지 소비 및 음향학적 소음이 적은 시스템이 필요하므로 연속적인 제어입력을 요구한다. 나아가, 구조와 파라메터의 관점에 있어서 용이한 설계 절차를 요구한다. 이 문제를 해결하기 위해서 진화 전략(Evolution Strategy : ES) 및 퍼지논리 제어기(Fuzzy Logic Controller : FLC)를 이용하는 지능형 장애물회피 알고리즘이 제안되었다. 제안된 알고리즘의 성능을 검증하기 위해 UFV 장애물회피가 수행되었다. 시뮬레이션 결과는 제안된 알고리즘이 실제 시스템에 존재하는 문제점들을 효과적으로 해결하고 있음을 보여준다.

• 한국자동차공학회논문집
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• 제23권5호
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• pp.478-485
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• 2015

Availability of the climbing angle information is crucial for the intelligent vehicle system. However, the climbing angle information can't be measured with the sensor mounted on the vehicle. In this paper, climbing angle estimation system is proposed. First, longitudinal acceleration obtained from gyro-sensor is compared with the actual longitudinal acceleration of the vehicle. If the vehicle is in yawing motion, actual longitudinal acceleration can't be approximated from time derivative of wheel speed, because lateral velocity and yaw rate affect actual longitudinal acceleration. Wheel speed and yaw rate can be obtained from the sensors mounted on the vehicle, but lateral velocity can't be measured from the sensor. Therefore, lateral velocity is estimated using unknown input observer with nonlinear tire model. Simulation results show that the compensated results using lateral velocity and yaw rate show better performance than uncompensated results.

• 로봇학회논문지
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• 제10권1호
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.1112-1117
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• 2010

The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance. Currently, we demonstrate developed railway crossing intelligence system at one crossing of Young-dong-seon line of Korail with Sea Train cockpit.

• 한국자동차공학회논문집
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• 제7권5호
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• pp.258-267
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• 1999

An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.