• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.37-43
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• 2004

Engine lubrication system is generally affected by vehicle driving conditions; acceleration, braking deceleration, and cornering. The oil supply system such as oil pan, baffle plate, and oil pick-up pipe should be optimized to cope with severe driving conditions. The main purpose of this paper is to understand the effect of the engine tilting angle on the oil supply system using engine tilting test rig. For the purpose, the oil pressure fluctuation and oil aeration in the main gallery are measured at various engine tilting angles. In addition, the oil flow is visualized by using transparent oil pan to investigate the cause of the formation of oil aeration. The test results show there is a strong correlation between the main gallery oil pressure fluctuation and oil aeration. It is also found that the visualization technique is helpful to stabilize the oil supply system at severe driving conditions.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.165-170
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• 2013

In this paper, we propose the information acquisition and analysis system for a vehicle driver in order to provide the safe driving environments. We first define the list of reckless driving behaviors and propose the recognition system, which recognizes the reckless behaviors, by using the acquired information. The collaboration among the information acquisition, the analysis, and the behavior comparison modules increases the accuracy of the recognition rate. Our system alarms to a vehicle driver in order to notify the potential to confront the dangerous situation due to the abnormal or reckless driving behaviors.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1990-1994
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• 2008

In this paper, we present a usable method of driving path in automatic guidance vehicle(AGV). The AGV is precisely driving to follow reference route. The Phileas in Netherland and Bi-modal tram in Korea have one wheel for the each side because of all wheels steering. For this reason, the loading area of wheels is very small. It is a disadvantage for asphalt load. The precise route tracking of vehicle can distort the flexible asphalt load. In this paper, we propose a driving method for alleviation of distortion on asphalt load.

• Journal of Power Electronics
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• v.12 no.6
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• pp.992-1002
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• 2012

In this paper, the series chopper based power train for electric vehicle is proposed for aiming the increase of one battery charge driving distance. Both the motor test bench based experiments and the chassis dynamo based experiments are tested and then analyzed for EV driving performance that the proposed power train with SAZZ chopper and Quasi-PAM control scheme is compared with or without the series chopper. It is confirmed through two kinds of experimental analyses that the series chopper power train for EV can be useful to extend the driving distance if the high efficiency and the low weight of chopper are satisfied.

• ETRI Journal
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• v.41 no.4
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• pp.506-514
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• 2019

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three-lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.

• Convergence Security Journal
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• v.22 no.2
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• pp.77-90
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• 2022

Domestic and foreign automakers compete to lead the autonomous vehicle industry through continuously developing self-driving technologies. These self-driving technologies are evolving with dependencies on the connection between vehicles and other objects such as the environment of cars and roads. Therefore, cyber security vulnerabilities become more likely to occur in the self-driving environment, so it is necessary to prepare for them carefully. In this paper, we model the threats in autonomous vehicles and make the checklist to securely countermeasure them.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.25-34
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• 2024

The paper investigates how the semiconductor and electric vehicle industries are addressing safety and security concerns in the era of autonomous driving, emphasizing the prioritization of safety over security for market competitiveness. Collaboration between these sectors is deemed essential for maintaining competitiveness and value. The research suggests solutions such as advanced autonomous driving technologies and enhanced battery safety measures, with the integration of AI chips playing a pivotal role. However, challenges persist, including the limitations of big data and potential errors in semiconductor-related issues. Legacy automotive manufacturers are transitioning towards software-driven cars, leveraging artificial intelligence to mitigate risks associated with safety and security. Conflicting safety expectations and security concerns can lead to accidents, underscoring the continuous need for safety improvements. We analyzed the expansion of electric vehicles as a means to enhance safety within a framework of converging security concerns, with AI chips being instrumental in this process. Ultimately, the paper advocates for informed safety and security decisions to drive technological advancements in electric vehicles, ensuring significant strides in safety innovation.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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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.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.130-139
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• 2011

In this paper, vehicle tracking algorithm using hue transformation in HIS color model is proposed. the proposed algorithm is installed on the road of the two horizontal virtual data sampling lines. The difference images are detected between the frame and the frame, respectively and also detected in the vehicle by using the hue color distribution to determine identity and lane changes. To examine the effectiveness of proposed algorithm, identification and velocity measurement for driving vehicle are evaluated. this evaluated results is shown by hue data of vehicle passing of two virtual data sample lines, and the velocity measurement for driving vehicle is less than 0.4% comparing with existing vehicle speed meter system.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.634-642
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• 2004

Unlike actual vehicles, a vehicle driving simulator is limited in kinematic workspace and bounded on dynamic characteristics. So it is difficult to simulate dynamic motions of a multi-body vehicle model. In order to overcome these problems, a washout algorithm which controls the workspace of the simulator within the kinematic limitation is needed. However, a classical washout algorithm contains several problems such as generation of wrong sensation of motions by filters in tilt coordination, requirement of trial and error method in selecting the proper cut-off frequencies, difficulty in returning the simulator to its origin using only high pass filters and etc. This paper proposes a new tilt coordination method as an algorithm which gives more accurate sensations to drivers. In order to reduce time for returning the simulator to its origin, a new washout algorithm that the proposed algorithm selectively onset mode from high pass filters and return mode from error functions is proposed. As a result of this study, the results of the proposed algorithm are compared with the results of classical washout algorithm through the human perception models. Also, the performance of the suggested algorithm is evaluated by using human perception and sensibility of some drivers through experiments.