• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.37-44
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• 2015

In this paper, we propose the assistance method to enable safe driving through analysis of dangerous driving behavior using real-time alarm by vehicle speed, azimuth data and smartphone. For this method, smartphone is receiving driving data from digital tachograph using communication. Safe driving habit is a very important issue to commercial vehicle because that driver's long time driving than other vehicle type driver. Existing methods are very inefficient to improve immediately dangerous driving habits during driving because proceed driving behavior analysis after the vehicle operation. We propose the new safe driving assistance method that can prevent traffic accidents by real-time and improve the driver's wrong driving habits through real-time dangerous driving behavior analysis and notification the result to the driver. We have confirmed that the method in this paper will help to improve driving habits and can be applied through the proposed method implementation and simulation experiment.

• Journal of the Semiconductor & Display Technology
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• v.10 no.4
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• pp.95-100
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• 2011

This paper proposes a new method of vehicle brake lights detection and recognition using an R-filtering. Firstly, the proposed method processes the R-filtering with the first input image and then with the second one in order to detect brake lights. Secondly, the method counts the number of red pixels and computes the mean value in each R-filtered image. The difference rates between the numbers of the red pixels and between the mean values of two images are defined in this paper. Through the analysis of the difference rates, it can recognize whether brake lights are turned on or off, and whether the vehicle ahead is being approached or not. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithm is quite successful.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.33-39
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• 2017

In recent days, crash safety system based on vehicle-to-vehicle communication (V2V) has been legislated. This V2V based safety system collects information from nearby vehicles to predict any crash possibility. Thus, it requires accurate and reliable data. Regularly updated features of Basic Safety Message(BSM) will be used to test validity of various elements included in the BSM. Then, the focus was made on whether values of these elements had notable differences compared to previous values. Through this paper, the validation tool was implemented and the result from V2V OBU experiment was used to identify problems in the current model and additional features that need to be implemented in V2V OBU for more accurate BSM.

• ETRI Journal
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• v.43 no.6
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• pp.1013-1023
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• 2021

In this study, we propose a practical path planning method that combines the A^* search algorithm and minimum snap trajectory generation. The A^* search algorithm determines a set of waypoints to avoid collisions with surrounding obstacles from a starting to a destination point. Only essential waypoints (waypoints necessary to generate smooth trajectories) are extracted from the waypoints determined by the A^* search algorithm, and an appropriate time between two adjacent waypoints is allocated. The waypoints so determined are connected by a smooth minimum snap trajectory, a dynamically executable trajectory for the quadrotor. If the generated trajectory is invalid, we methodically determine when intermediate waypoints are needed and how to insert the points to modify the trajectory. We verified the performance of the proposed method by various simulation experiments and a real-world experiment in a forested outdoor environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.1-10
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• 2007

As drivers spend more time in their cars, perception of driving a vehicle turns from utilizing a transportation means into residing in a personal space or even in moving office. Such a perception renders automobile manufacturers incorporate more vehicle functions, especially in-vehicle information systems As the number of system functions increases, the complexity of control and 2 types of display menus were designed after a literature review and a market analysis. With these controls and display menus, the experiment was performed to look into the difference of driver performance and preference on the integrated vehicle control type. Finally, the study suggests the integrated vehicle control type to minimize driver's cognitive load, and to use various functions efficiently. The study also discusses the practical use of the final integrated vehicle control type.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1231-1237
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• 2006

The vibration of a running railway vehicle can be classified on lateral, longitudinal and vertical motions. The important factor on the stability and ride quality of a railway vehicle is the lateral motion. The contact between wheel and rail with conicity influences strongly on the lateral motion. In this study, an experiment for the vibration of a running railway vehicle was performed using a of the scale model of a railway vehicle. Also, the effects on the car-body, bogie and wheelset were examined for the weight and the stiffness of the second suspension system. The experimental results showed that the lateral vibration increases as the wheel conicity and stiffness of the second suspension system increase. And the lateral vibration of the bogie increases as the mass ratio between car-body and bogie increases. Also, the lateral vibration of the wheel becomes high at low speed, while the wheel of 1/20 conicity makes severe vibration at high speed running.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.18-27
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• 2020

In order to estimate the launch point of a high-speed vehicle, predicting the various characteristics of the vehicle's movement, such as drag and thrust, must be preceded by the estimation. To predict the various parameters regarding the vehicle's characteristics, we build the IMM filter specialized in predicting the parameters of the post-launch phase based on flight dynamics. Then we estimate the launch point of the high-speed vehicle using Inverse Dynamics. In addition, we assume the arbitrary error level of the radar for accuracy of the prediction. We organize multiple-dimensioned IMM structures, and figure out the optimal value of parameters by comparing the various IMM structures. After deriving the optimal value of parameters, we verify the launch point estimation error under certain error level.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.8 s.227
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• pp.1116-1124
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• 2004

In these days, a vehicle simulator has been developed with a VR(Virtual Reality) system. A VR system must provide a vehicle simulator with natural interaction, sufficient immersion and realistic images. In addition, a VR system must present a driver with the realistic driving situation. To achieve these, it is important to obtain a fast and uniform rendering performance regardless of the complexity of virtual worlds. In this paper, the factors to improve the reality for the VR based vehicle simulator have been investigated. For the purpose, the modeling and the rendering methods which offer an improved performance for complex VR applications as the 3D road model have been implemented and verified. Then, we experiment on the influence of graphic and sound factors to the driver, and analyze each result for improving the reality such as the driver's viewport, the form of texture, the lateral distance of the side object, and the sound effect. These factors are evaluated on the driving system which is constructed for qualitative analysis. The research results could be used for improving the reality of the VR based vehicle simulator.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.92-97
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• 2012

In the present the usage of bicycle has increased steeply due to well-being and convenient way of movement. In car to bicycle accident, the throw distance of bicycle is very important factor for estimating collision situation. In this study, simulations and collision tests in actual car to bicycle were executed for obtaining throw distance of bicycle. The simulations were executed by PC-CRASHTM s/w with vehicle of sedan type. Sand bags were used for the behavior of bicyclist instead of dummy and factors considered were vehicle velocity, the crashed angles and part of bicycle to vehicle, and bicycle was adult type. From the results, the throw distances of tire collision of 00 was longer than that of 450 tire crash, and the throw distances of 900 frame crash were longer than those of 450 frame crash. With based on actual crash tests and simulations, restitution coefficient of between vehicle and bicycle was estimated as 0.1. Finally the increaser vehicle velocity the longer the throw distances of bicycle and the simulation results were relatively good agreement to the results of experiment.