• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.55-63
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• 2010

This paper describes performance improvement of GPS/DR Integration system using area decision algorithm and vehicle movement information. In GPS signal blockage area, i.e., tunnel and underground parking area, DR sensor errors are accumulated and navigation solution is gradually diverged. We use the car movement information according to moving area to correct the DR sensor error. Also, vehicle movement is decided as stop, straight line, turn and movement changing region through DR sensor data analysis. The car experiment is performed to verify the supposed method. The results show that supposed method provides small position and heading error than previous method.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.193-196
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• 2007

Recent advancements of wireless communication technology and miniaturization technique enables the implementation of wireless sensor network(WSN) using smart sensors. In addition, the research on the application of WSN to various fields of our daily life is performing briskly[1]. In this paper, we described the implementation of campus vehicle management system using wireless sensor nodes as an application of WSN. To do this, we have investigated the functions of commercial wireless sensor nodes such as transmission power control and node identification. We also proposed the architecture and operation procedure for the real system implementation.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.14-23
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• 2005

In this paper we propose a sensor fusion method for the navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with. biases and measurement noise, are investigated with theoretically data from MOERI's SAUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system commonly used aboard underwater vehicle.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.

• Journal of IKEEE
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• v.22 no.2
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• pp.518-521
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• 2018

IVN (in-vehicle network) connects various electronic modules in the vehicles. It requires real-time, low noise, high reliability, and high flexibility. It includes CAN (controller area network), CAN-FD (CAN flexible data rate), FlexRay, LIN (local interconnect network), SENT (single edge nibble transmission), and PSI5 (peripheral sensor interface 5). In this paper, their operation priciples, target applications, and pros and cons are explained.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.938-941
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• 2003

In this paper we develop an equipment which prevents vehicles from overheating their inside due to exposure to direct sunlight in summer. Overheating of inside vehicle may give rise to accidents, for instances, dying from suffocation, the deformation of its internal equipment and the explosion from the cracks of its internal parts etc.. The equipment is operated under no starting engine. We adjust the overheating of the inside vehicle by operating the equipment. This equipment checks the temperature of the inside vehicle using temperature sensor. If the temperature increases more than reference temperature(a condition which can be given by the driver), the equipment will operate until the temperature of the inside decreases to the given temperature. Its power is obtained from solar cell. So the equipment keeps away overheating accidents as well as provides the drivers with optimized condition. And also it increases the ability of original car battery through solar cell.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.16-24
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• 2013

Some GM (General Motors) vehicles are using a GMLAN (General Motors Local Area Network) communication protocol for control and diagnostics. The airbag control module uses vehicle speed information from the GMLAN to record the vehicle speed as pre-crash information. In order to use the vehicle speed information for crash reconstruction purposes, it helps to be able to understand the accuracy of the data. The actual vehicle speed is not expected to be the same as the GMLAN indicated speed in some situations like a spin or if there is hard braking. This paper compares the actual vehicle speed and vehicle speed information during specific vehicle maneuvers. Actual vehicle speed is calculated from a GPS sensor, while GMLAN vehicle speed is calculated from transmission output sensor by the Engine control module (ECM). Vehicle maneuvers defined as Mode #1, Mode #2, Mode #3. The Mode #1 maneuver simulates wheel lock-up and skidding f by hard-braking at a specific speed. The Mode #2 maneuver simulates a 90degree turn using a J-turn maneuver at a specific speed. The Mode#3 maneuver simulates a 180 degree turn using a spin type of maneuver at a specific speed. The study then compares the GMLAN speed and GPS speed to see what speed difference exists between them. The results of this paper are applicable to GM vehicles only. This paper catalogs the performance and limitations of two vehicles as useful reference for crash reconstructions where there is a need to understand the speed indicated in the pre-crash section of the SDM data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1067-1070
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• 2003

In this paper, we present a remote measurement system for the wireless monitoring of ECU Sensor Signals of vehicle. In order to measure the ECU sensor signals, the interface circuit is designed to communicate ECU and designed terminal wirelessly according to the ISO, SAE regulation of communication protocol standard. A micro-controller 80C196KC is used for communicating ECU sensor signals. ECU sensor signals are transmitted to the RF-wireless terminal that was developed using the micro controller 80386EX. LCD, and RF-module. 80386EX software is programmed to monitor the ECU sensor signals using the Borland C++ compiler in which the half duplex method was used for the RS232 communication. The algorithms for measuring the ECU sensor signals are verified to monitor ECU state. At the same time, the information to fix the vehicle's problem can be shown on the developed monitoring software. The possibility for remote measurement of ECU sensor signals using 80386EX is also verified through the developed systems and algorithms.