• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1405-1411
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• 2011

It is very often for the experienced diesel locomotive drivers to identify the proper replacing time for the fuel adjustment tube only based on their experience. Because of that, sometimes the locomotive's fuel is burned out due to the unnecessary torque. Or sometimes, the locomotive does not operate with its accelerating performance because the fuel is not supplied at the appropriate moment. Meanwhile, recent typical auto vehicles provide drivers with the average fuel efficiency and the instant fuel efficiency in real-time. By providing the real time display mentioned above, it is one of the good examples that those drivers, who had driven their cars not properly and used a lot of fuel with their bad driving habits, obtain the efficient driving pattern by continuous educating effect. Similarly, if the diesel locomotive provides the train driver with the optimal driving pattern within a certain driving section, it will be effective for fuel saving. It is possible to make the most effective driving pattern by performing the repeated trial running especially for the railway because the track's operating routes, its grades, and etc are relatively precise. This research analyzes the result data which was obtained by many times trial running on the identical section after equipping the fuel use measuring device to a certain test vehicle, and confirms the fuel saving effect depending on the driving pattern along the test section. At the same time, the research to establish the optimal driving pattern was progressed.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.227-235
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• 2006

In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.237-244
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• 2022

Eco-driving of vehicles today presents an advantage that aims to reduce energy consumption and limit CO2 emissions. The application for this option is possible to older vehicles. In this paper, we propose an efficient implementation for IoT (Internet of Things) system for controlling vehicle components that affect the quality of driving (acceleration, braking, clutch, gear change) via Smartphone using Wi-Fi and BLE as communication protocol. The user can see in real-time data from sensors that control driver action on vehicle driving systems such as acceleration, braking, and vehicle shifting through a web interface. Thanks to this communication, the user can control his driving quality and, hence, eco-driving can be achieved

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.283-291
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• 2013

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.109-118
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• 1999

A graphic software is one of the most important components of the vehicle simulator. To increase a visual reality of the simulator, the graphic software should require several technologies such as three-dimensional graphics, graphic modeling of the vehicle and the environment, drivers biomechanical models, and real-time data processing. This study presents a real time graphic driving simulator of a construction vehicle. The graphic simulator contains the three models of the construction vehicle, the human, and the environment, and employes a neural network approach to decrease an on-line dynamic computation. An excavator model is represented using an object-oriented paradigm and contains the detailed information about a real-size vehicle. The human model is introduced for objective visual evaluations of the developed excavator model. Since the environment model plays an important role in a real-time simulator, a block-based approach is implemented and a text format is utilized for easier construction of environment. The simulation results are illustrated in order to demonstrate the applicability of developed models and the neural network approach.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.17-24
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• 2010

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.109-114
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• 2004

This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) system using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.51.2-51
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• 2001

A vehicle driving simulator is a virtual reality device which makes a human being feel as if the one drives a vehicle actually. The driving simulator is effectively used for studying interaction of a driver-vehicle and developing the vehicle system of new concepts. The driving simulator consists of a motion platform, a motion controller, a visual and audio system, a vehicle dynamic analysis system, a vehicle operation system and etc. The vehicle dynamic analysis system supervises overall operation of the simulator and also simulates dynamic motion of a multi-body vehicle model in real-time. In this paper, the main procedures to develop the driving simulator are classified by 4 parts. First, a vehicle motion platform and a motion controller, which generates realistic motion using a six degree of freedom Stewart platform driven hydraulically. Secondly, a visual system generates high fidelity visual scenes which are displayed on a screen ...

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.33-39
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• 2017

In this paper, we propose a method which implements warning to drivers through real-time analysis of risky and unexpected driver and vehicle behavior using only a smartphone without using data from digital tachograph and vehicle internal sensors. We performed the evaluation of our system that demonstrates the effectiveness and usefulness of our method for risky and unexpected driver and vehicle behavior using three information such as vehicle speed, azimuth and GPS data which are acquired from a smartphone sensors. We confirmed the results and developed the smartphone application for validate and conducted simulation using actual driving data. This novel functionality of the smartphone application enhances drivers' situational awareness, increasing safety and effectiveness of driving.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.4
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• pp.60-67
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• 2012

Most of a driving cycle is used to measure fuel consumption (FC) and emissions for a specified vehicle. A driving cycle was reflected geography and traffic characteristics for each country, also, driving pattern is affected these parameters such as vehicle dynamics, FC and emissions. Therefore, this study is an attempt to develop a driving cycle for military operational area. The proposed methodology the driving cycle using micro-trips extracted from real-world data. The methodology is that the driving cycle is constructed considering important parameters to be affected FC. Therefore, this approach is expected to be a better representation of heterogeneous traffic behavior. The driving cycle for the military operational area is constructed using the proposed methodology and is compared with real-world driving data. The running time and total distance of the final cycle is 1461 s, 13.10 km. The average velocity is 32.25 km/h and average grade is 0.43%. The Fuel economy in the final cycle is 5.93 km/l, as opposed to 6.10 km/l for real-world driving. There were about 3% differences in driving pattern between the final driving cycle and real-world driving.