• Asia pacific journal of information systems
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• v.32 no.4
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• pp.916-944
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• 2022

Artificial Intelligence has been a conceptual area for several decades. It has been studied extensively through experiments by the Information Systems community. When Information Systems supported with Information Technology became all pervasive in business and other allied areas, gradually the advancements in Artificial Intelligence also emerged as innovations across domains. Artificial Intelligence by definition is expected to substitute Human Intelligence, thereby making a huge space for innovation. In fact, all processes effected by human intelligence are liable to be replaced by AI which in itself is a massive innovation space. This paper will study the publication's repository (Scopus and Google Scholar from 1983 till 2021) in the area of Artificial Intelligence and innovation, then analyze the trend to gain insight into the evolution of AI as a vehicle for innovation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.706-712
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• 2012

This paper presents a sensor network and operation for multiple autonomous navigation platform and transport service. Multiple platform navigate with inside sensors and outside sensors while acquiring and process some useful information. Each platform communicates each other by navigational information through central main server. Efficient sensor network systems are considered for the scenario which some passengers call the service and the vehicle accomplish its transport service by transporting each caller to the destination by autonomous manners. In the scenario, all vehicles perform a role of sensor system to the central server and the server handles each information and integrate with faster procedure in the wireless 3G network.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.71-76
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• 2001

This paper deals with an estimation method for sideslip angle by using an unknown disturbance observation technique in 4WS passenger car systems. Firstly, a 4WS vehicle model with 3DOF is derived under the constant velocity and same tyres properties. The vehicle dynamics is transformed into the linear state space model with considering the external disturbances. Secondly, and unknown disturbance observer is introduced and its property which estimating the states of system without any disturbance information is shown. Lastly, the estimated sideslip angle of the 4WS vehicle system is verified through numerical simulation.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.49-54
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• 2016

In this paper, the confirmation method of target detection for the vehicle mounted metal detector (MD) has been described. The vehicle mounted MD with the arrayed 6 coils to detect the width of 2.4 m was demonstrated. It is important and necessary to inform the location of the objects detected by the MD. The confirmation method of target detection was verified by using the MD GUI and the analysis of the receive signal processing. The receive signal processing is performed by comparing the threshold and the difference of the signal calibrated at initial location and the signal detected at present location.

• International Journal of Automotive Technology
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• v.7 no.4
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• pp.469-475
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• 2006

In this paper, an optimal suspension system with preview of the road input is synthesized for a half tracked vehicle. The main goal of this research is to improve the ride comfort characteristics of a fast moving tracked vehicle in order to maintain the driver's driving capability. Several different kinds of preview control algorithms are evaluated with active or semi-active suspension systems. The road information estimated from the motion of the 1st road-wheel is adequate to make the best use of the preview control algorithm for tracked vehicles. The ride-comfort characteristics of the tracked vehicle are more dependent on pitching angular acceleration than heaving acceleration. The pitching motion is reduced by the suspension system with hard outer suspensions and soft inner suspensions. Simulation results show that the performance of sky-hook algorithms for ride comfort nearly follow that of full state feedback algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.809-817
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• 2008

This paper describes an obstacle detecting system of an unmanned ground vehicle (UGV). The unmanned ground vehicle is consists of several systems such as vehicle control system, navigation system, obstacle detecting system and integration system. Among these systems, the obstacle detecting system is a driving assistance system of UGV. Through the UGV is driving, the system detects obstacles such as cars, human, tree, curb and hills and then send information of obstacles position to integration system for safety driving. In this research, the obstacle detecting system is composed of 5 laser scanners and develop algorithms of detecting obstacles, curb, uphill and downhill road.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.10-24
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• 2014

In-vehicle warning information systems(IWIS) is an effective countermeasure for preventing traffic crashes. It provides drivers with warnng messages about upcoming hazards to draw proper evasive maneuvering. This study developed a methodology for evaluating the effectiveness of IWIS based on an integrated index to identify driver's responsive behavior. The proposed index consists of characteristics of longitudinal and lateral behavior of vehicle maneuverings. Also, a method to assign mixed-weights in the context of multi-criteria decision making framework was adopted to develop the evaluation method. It is expected that the outcome of this study is useful in designing more effective in-vehicle warning information systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.232-237
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• 2009

Active safety vehicle devices are getting more attention recently. To prevent traffic accidents, the environment in front and even around the vehicle must be checked and monitored. In the present applications, mainly camera and radar based systems are used as sensing devices. Laser scanner, one of the sensing devices, has the advantage of obtaining accurate measurement of the distance and the geometric information about the objects in the field of view of the laser scanner. However, there is a problem that detecting object occluded by a foreground one is difficult. In this paper, criterions are proposed to manage this problem. Simulation is conducted by vehicle mounted the laser scanner and multiple-hypothesis algorithm tracks the candidate objects. We compare the running times as multi-hypothesis algorithm parameter varies.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.16-25
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• 1997

This paper shows the development of the high accuracy vehicle positioning algorithm using the differential technique in vehicle tracking systems form the existing vehicle position which is acquired from the global positioning system (GPS). The control center receives the satellite ephemerise data and pseudorange correction from the reference station, and vehicle position from the moving vehicle. The pseudorange is calculated with the satellite position and the vehicle position, and corrected by pseudorange correction. Using this corrected pseudorange and kalman filter, more improved vehicle positioning data were obtained.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.