• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.3
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• pp.251-260
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• 2009

Hybrid locomotive UGV with actively articulated legs along with wheeled ends has high traversability to travel over rough terrain. The behavior control method was usually adapted for the controlling of the suspension configuration which determines the traversability of the UGV. In this study, we are proposing a method of configuration planning of the legs without any detail geometric data about the terrain. The terrain was estimated by the traces of each wheel and the leg configurations for the desired posture of the vehicle were set up against the constraints of the terrain. Also, an optimal leg configuration was calculated based on the quasi-static stability and power consumption, and plans for the leg behavior were made. Validity of the proposed method was checked by simulations using some off-the-shelf programs, and showed that the orientation control without geometric features of terrains and simplification of the behavior planning for obstacle negotiation were possible.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.229-238
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• 2009

In this paper, AWS ECU test method, which is considering behavior of a Bi-modal tram, is described. In order to evaluate the performance of an electronic automotive ECU, the method which combines HILS (Hardware In the Loop Simulation) and RBT (Requirement Based Testing) is introduced. HILS is the method to predict the behavior of a vehicle adopting an ECU. The behavior of a Bi-modal tram can be analyzed by using the vehicle dynamic model. Requirement Based Testing compare the outputs of a real system with a virtual electronic unit (oracle) which created by the requirements. Rear axles of the Bi-modal tram are independently controlled by two AWS ECU. Especially, swing out can happen when an articulated vehicle is operated in the curved road. Therefore dynamic behaviour of a Bi-modal tram is considered at this situation. Through this study, the reliability of ECU can be verified economically and safely using the proposed test method before conducting the track test.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.723-728
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• 2022

This study is a method for evaluating and quantifying driver's dangerous driving behavior. The quantification method calculates various driving information in real time after starting the vehicle operation such as the time that the vehicle has been continuously driven without a break, overspeed, rapid acceleration, and overspeed driving time. These quantified risk of driving behavior values can be individually provided as a safe driving index, or can be used to objectify the evaluation of a group of drivers on roads, or vehicle groups such as cargo/bus/passenger vehicles.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.619-624
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• 2006

This paper presents design of a vehicle stop-and-go cruise control strategy based on analyzed results of the manual driving data. Human drivers driving characteristics have been investigated using vehicle driving data obtained from 100 participants on low speed urban traffic ways. 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 feel comfortable to the human driver under low speed stop-and-go driving conditions. Vehicle following characteristics of the cruise controlled vehicle have been investigated using a validated vehicle simulator and real driving radar sensor data.

• Journal of Mechanical Science and Technology
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• v.19 no.4
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• pp.993-1000
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• 2005

A vehicle cruise control strategy designed based on human drivers driving characteristics has been investigated. Human drivers driving patterns have been investigated using vehicle driving 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 feel comfortable to the human driver. Vehicle following charac­teristics of the cruise controlled vehicle have been investigated using real-world vehicle driving test data and a validated simulation package.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.431-437
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• 2007

This paper describes the dynamic modeling of a railway vehicle when it is under braking force. It is important for the enhancement of braking performance to establish a proper dynamic model of a railway vehicle because the braking performance is affected by some dynamic forces generated by a railway vehicle when it undergoes braking. In this paper, a dynamic model for one vehicle is suggested to compute the dynamic behavior of a railway vehicle in the HILS(Hardware In-the-loop Simulation) system for the railway vehicle braking devices. To simplify the dynamic model, friction between a wheel and a rail is assumed that there exist only the static and the dynamic friction forces. Static friction coefficient is also assumed to be a function of the running speed. Some simulations are carried out with various braking forces, and the braking characteristics according to the change of the braking force are discussed. This study can provide some fundamental results to construct the HILS system for braking devices of a railway vehicle.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.487-489
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• 1998

To evaluate vehicle performances and driving behavior of a vehicle, it is necessary to acquisit and analyze vehicle data during the vehicle driving, which affect fuel economy and emissions. An in-vehicle data acquisition system, which is called Mode Survey System(MOSS), is designed and developed to analyze the traffic and driving patterns of the vehicle. MOSS is a stand-alone system based on the 68HC11 MCU. MOSS logs various data relating to powertrain and vehicle driving such as vehicle speed, engine RPM, gear position, brake, clutch, fuel consumption, and others. The driving patterns are dependent on the driver's habit and the road and traffic conditions, these driving patterns would be able to make a official driving mode to be used in emission, fuel efficiency, shift survey, catalyst durability, and other tests using the analyzed driving patterns.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1631-1638
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• 2007

In this paper, a modeling for the dynamic behavior of a train vehicle is suggested for the prediction of the braking characteristics. In the dynamic modeling, effects of the primary and secondary suspension elements are considered and interactions between two vehicles are also estimated. This study can offer some fundamental results for a further research to enhance the braking performance using active braking control.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.437-446
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• 1999

The structural behavior of the composite material light rail vehicle body are investigated. Composite material is very useful for light rail vehicle structure due to its high specific strength and lightweight characteristics. The main carbody is made of aluminum alloy. The side wall and roof with composite panels can reduce total vehicle weight about 2000kg. In addition, with the lower density of the foam, enhances lightness in the panel and to save the operation expenses. The finite element analysis code, ANSYS is used to evaluate the stability of the body structure under the various load conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.45-56
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• 2007

Automatic tracking of vehicles is important to accurately estimate the traffic information including vehicle speeds in video-based traffic measurement systems. Because of the limited field of view, the range of visual tracking with a single camera is restricted. In order to enlarge the tracking range for better chance of monitoring the vehicle behaviors, a tracking with consecutive multiple video sequences is necessary. This parer proposes a carefully designed rule-based vehicle racking scheme and apply it for the tracking for two well synchronized video sequences. In the scheme, almost all possible cases that can appear in the video-based vehicle tracking are considered to make rules. Also, the rule based scheme is augmented with Kalman filter. The result of tracking can be successfully used to collect data such as temporal variation of vehicle speed and behavior of individual vehicle behaviors in the enlarged tracking region.