• ETRI Journal
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• v.36 no.6
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• pp.968-978
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• 2014

Autonomous vehicle technology based on information technology and software will lead the automotive industry in the near future. Vehicle localization technology is a core expertise geared toward developing autonomous vehicles and will provide location information for control and decision. This paper proposes an effective vision-based localization technology to be applied to autonomous vehicles. In particular, the proposed technology makes use of numerical maps that are widely used in the field of geographic information systems and that have already been built in advance. Optimum vehicle ego-motion estimation and road marking feature extraction techniques are adopted and then combined by an extended Kalman filter and particle filter to make up the localization technology. The implementation results of this paper show remarkable results; namely, an 18 ms mean processing time and 10 cm location error. In addition, autonomous driving and parking are successfully completed with an unmanned vehicle within a $300m{\times}500m$ space.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.9-15
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• 2014

In the ubiquitous computing environment, a ubiquitous vehicle will be a communication node in the vehicular network as well as the means of ground transportation. It will make humans and vehicles seamlessly and remotely connected. Especially, one of the prominent services in the ubiquitous vehicle is the vehicle remote operation. However, mutual-collaboration with the in-vehicle communication network, the vehicle-to-vehicle communication network and the vehicle-to-roadside communication network is required to provide vehicle remote operation services. In this paper, an Internet-based human-vehicle interfaces and a network architecture is presented to provide remote vehicle control and diagnosis services. The performance of the proposed system is evaluated through a design and implementation in terms of the round trip time taken to get a vehicle remote operation service.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.3
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• pp.119-128
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• 1995

A driver-vehicle model means the integrated dynamic model that is able to estimate the steering wheel angle from the driver's desired path based on the dynamic characteristics of the driver and vehicle. In this paper, the dynamic characteristics of several four-wheel steering systems with the simultaneously steerable front and rear wheels are investigated and compared by means of the driver-vehicle model. Especially, the presented analysis results are obtained by using the ISO test codes such as lane change, double lane change and slalom, and the effects of the driver's steering response time and vehicle speed are examined on the responsiveness and stability of vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.115.2-115
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• 2002

A real-time vehicle simulation system is a key element of a driving simulator because accurate prediction of vehicle motion with respect to driver input is required to generate realistic visual, motion, sound and proprioceptive cues. In order to predict vehicle motion caused by various driving actions of the driver on board the simulator, the vehicle model should consist of complete subsystems. On this paper, a tracked vehicle dynamic model with high efficiency and effectiveness is introduced that has been implemented on a training driving simulator. The multi-body vehicle model is based on recursive formulation and has been automatically generated from a symbolic computation package develop...

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.32-38
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• 2006

A vehicle adaptive cruise control strategy based on human drivers' driving characteristics has been investigated. Human drivers driving characteristics have been analyzed using vehicle test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would reduce the workload of the human driver. Vehicle following characteristics of the cruise controlled vehicle have been compared to real-world driving radar sensor data of human drivers using a validated vehicle simulator. and compare nominal cruise control and adaptive cruise control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.265-272
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• 1996

In this paper, attitude computation algorithm for a strap down ARS(Attitude Reference System)of an underwater vehicle has been studied. Attitude errors o the ARS using low-level gyroscopes tend to increase with time due to gyroscope errors. To cope with this problem, a mixing algorithm of accelerometer aided attitude computation has been developed. The algorithm can successfully bound the error increase for cruising motion, but it gives instantaneously large errors when a vehicle maneuvers. To improve the performance in case of vehicle's maneuver, a new attitude computation mixing algorithm complying state of vehicle and to manage the adjustment of the gains which are invariant in the existing algorithm. In addition, a gain scheduling method is applied to fuzzy inference composition process for real-time computation. Monte Carlo simulation results show that the proposed algorithm provides better performance than the existing algorithm.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.729-734
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• 2004

The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. The management of vehicles' location in most conventional vehicle tracking system has some critical defects when it deals with data which are continuously changed. It means the conventional vehicle tracking system based on the conventional database is unable eventually to cope with the environment that should manage the frequently changed location of vehicles. The important things in the evaluation of the vehicle tracking system is to determine the threshold of cost of database ,update period and communication period between vehicles and the system. In other words, the difference between the reallocation of vehicle and the data in database can evaluate the overall performance of vehicle tracking systems. Most of the previous works considers only the information that is valid at the current time, and is hard to manage efficiently the past and future information. To overcome this problem, the efforts on moving objects management system(MOMS) and uncertainty processing have been started from a few years ago. In this paper, we propose an uncertainty processing model and system implementation of moving object that tracks the location of the vehicles. We adopted both linear-interpolation method and trigonometric function to chase up the location of vehicles for the past time as well as future time, respectively. We also explain the comprehensive examples of MOMS and uncertainty processing in parcel application that is one of major application of e-Logistics domain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2098-2114
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• 2021

Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.71-81
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• 2022

In order for electro-optical tracking system (EOTS) to have accurate target coordinate, accurate navigation results are required. If an integrated navigation system is configured using an inertial measurement unit (IMU) of EOTS and the vehicle's navigation results, navigation results with high rate can be obtained. Due to the time-delay of the navigation results of the vehicle in the EOTS and scale factor errors of the EOTS IMU in high-speed and high dynamic operation of the vehicle, it is much more difficult to have accurate navigation results. In this paper, an integrated navigation system of EOTS which compensates time-delay and scale factor error is proposed. The proposed integrated navigation system consists of vehicle's navigation system which provides time-delayed navigation results, an EOTS IMU, an inertial navigation system (INS), an augmented Kalman filter and integration Kalman filter. The augmented Kalman filter outputs navigation results, in which the time-delay of the vehicle's navigation results is compensated. The integration Kalman filter estimates position, velocity, attitude error of the EOTS INS and accelerometer bias, accelerometer scale factor error, gyro bias and gyro scale factor error from the difference between the output of the augmented Kalman filter and the navigation result of the EOTS INS. In order to check performance of the proposed integrated navigation system, simulations for output data of a measurement generator and land vehicle experiments were performed. The performance evaluation results show that the proposed integrated navigation system provides more accurate navigation results.