• Journal of Auto-vehicle Safety Association
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• 제11권1호
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• pp.7-16
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• 2019

There are trying to reduce damage from automobile accident in many countries. In many automobile companies, there have been active study on development of ADAS (Advanced Driver Assistance Systems) for commercialization, in order to reduce damage from automobile accident. ADAS is the system providing convenience and safeness for drivers. Generally, ADAS is composed of ACC (Adaptive Cruise Control), LKAS (Lane Keeping Assist System), and AEB (Autonomous Emergency Braking). AEB of the ADAS, it is an autonomous emergency braking system and it senses potential collide and avoids or degrades it. Therefore AEB plays a significant role in reducing automobile accident rate. However, AEB safety evaluation method is not established not yet. For this reason, this study suggests safety evaluation scenarios with adding cut-in, sensor malfunctioning scenario that scenario domestic street conditions considered as well as original standard AEB scenario of Euro NCAP for establishment of safety evaluation method of AEB. And verifying validity of suggested scenario by comparing the calculated values of the theoretical formulas presented in the previous study with results of the actual vehicle test.

• Journal of Auto-vehicle Safety Association
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• 제14권3호
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• pp.23-29
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• 2022

Among the various functions of ADAS (Advanced Driver Assistance System), the most important and representative function to the safety of vehicle passengers is AEB (Autonomous Emergency Braking system). In South Korea, laws are in progress from 2022 for making it mandatory for passenger vehicles to be installed. And as AEB-equipped vehicles continues to increase in the future, the demand for accident analysis related to the AEB function is expected to increase in the future. In order to find out the operating limits of AEB, it is necessary to consider the situations exceeding the standards covered by EuroNCAP. Therefore we have performed four experiments in this study, including situations encountered in real-word traffic conditions, i.e., an oblique stop of Global Vehicle Target (GVT) and ADAS sensor failures. These experimental results are expected to be of great help in accurate and reliable accident analysis by considering them when analyzing traffic accidents for ADAS vehicles.

• IEMEK Journal of Embedded Systems and Applications
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• 제17권1호
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• pp.41-49
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• 2022

This paper proposes a novel lane detection algorithm based on inverse perspective transformation and machine learning in lightweight embedded system. The inverse perspective transformation method is presented for obtaining a bird's-eye view of the scene from a perspective image to remove perspective effects. This method requires only the internal and external parameters of the camera without a homography matrix with 8 degrees of freedom (DoF) that maps the points in one image to the corresponding points in the other image. To improve the accuracy and speed of lane detection in complex road environments, machine learning algorithm that has passed the first classifier is used. Before using machine learning, we apply a meaningful first classifier to the lane detection to improve the detection speed. The first classifier is applied in the bird's-eye view image to determine lane regions. A lane region passed the first classifier is detected more accurately through machine learning. The system has been tested through the driving video of the vehicle in embedded system. The experimental results show that the proposed method works well in various road environments and meet the real-time requirements. As a result, its lane detection speed is about 3.85 times faster than edge-based lane detection, and its detection accuracy is better than edge-based lane detection.

• Journal of the Ergonomics Society of Korea
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• 제36권2호
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• pp.87-108
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• 2017

Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제20권5호
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• pp.18-34
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• 2021

Pedestrian deaths in Korea due to traffic accidents are 40 percent of the fatalities in traffic accidents, which is about twice the average of OECD member countries. To reduce severe pedestrian accidents, it is necessary to apply the accident reduction measures to high-risk drivers (novice, elderly, and commercial vehicle drivers) who are more likely to cause traffic accidents than general drivers. Therefore, this study analyzed the effect of safe driving education on high-risk drivers' behavior. Here, the safe driving education is chosen as the measure to reduce traffic accidents. As part of the study, sudden pedestrian crossing situations were implemented in the driving simulator, and the vehicle trajectory data were collected to compare the driving behavior before and after the education. Most surrogate safety measures showed no improvement in the driving behavior of novice and elderly drivers, and the effect of safe driving education was found to be significant only in the group of commercial vehicle drivers. The results implied that additional measures such as pedestrian safety infrastructure and driver assistance systems, apart from the safe driving education, may be needed for novice and elderly drivers to reduce pedestrian accidents caused by them. With the findings mentioned above, this study is expected to provide a foundation to establish a plan to reduce pedestrian accidents caused by high-risk drivers.

• Journal of the Ergonomics Society of Korea
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• 제34권3호
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• pp.247-264
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• 2015

Objective: The purpose of this study is to determine the priority of information presentation and the effective menu type to be placed in the center of a gauge cluster display for commercial trucks and to present a set of ergonomic designs for the gauge cluster display. Background: An effective ergonomic design is specifically needed for the development of the gauge cluster display for the commercial trucks, because more diverse and heavier information is delivered to truck drivers, compared to the information to passenger car drivers. Method: First, all the information that must be shown on the commercial truck display was collected. Then, the severity, frequency of use, and display design parameters were evaluated for those information by commercial truck drivers. Next, an analysis on the information attributes and the heuristic evaluation utilizing the display design principles were carried out. According to the results, a design alternative of the main screen to be displayed was constructed by priority. A comparative analysis between the alternative and existing main screens was also conducted to see the efficacy of the designs. Lastly, we conducted an experiment for the selection of menu type. The experiment was conducted using the driving simulator with an eye-tracking device. The independent variables were four types of the menu reflecting the commercial truck characteristics such as grid type, icon type, list type, and flow type. We measured preference, total execution time, the total duration of fixation on the gauge cluster area, and the total number of fixation on the gauge cluster area as dependent variables. Results: Four types of driver convenience information and six types of driver assistance information were selected as the information to be placed primarily on the main screen of the gauge cluster. The Grid type was the most effective among the menu types. Conclusion: In this study, the information that appears on the main screen of the display, the division of the display and the design of the menu type for commercial truck drivers were suggested. Application: This study is expected to be utilized as guidelines on the ergonomic design of a gauge cluster display for commercial trucks.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제40권1호
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.

• Journal of the Korea Society for Simulation
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• 제19권1호
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• pp.23-31
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• 2010

Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.

• Journal of Internet of Things and Convergence
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• 제10권5호
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• pp.165-171
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• 2024

The colored road surface guide lines have been proven to significantly reduce the occurrence of traffic accidents. However, these guide lines have been currently applied sequentially only on roads that meet the installation criteria designated by the Ministry of Land, Infrastructure, and Transport. Furthermore, existing navigation systems such as legacy navigation and HUD (Head-Up Display) have demonstrated errors or ambiguities in delivering route information, highlighting the need for a clearer method of guiding drivers. In this paper, we propose a lane detection and masking technique that integrates the features of AR HUD (Augmented Reality Head-Up Display), a technology gaining attention in vehicle convenience systems, with the characteristics of colored road surface guide lines. The proposed technique detects and classifies lanes based on their color and lane detection results, then performs road masking using the classified lanes. Experimental results show that the proposed technique masked approximately 70% of the lane area. This enables drivers to receive real-time images of the masked route they should follow, offering an experience similar to constantly visualizing colored road surface guide lines. We expect that this approach will provide more intuitive information and improve driver convenience. Future advancements in this masking technique will further contribute to enhancing both convenience and safety for drivers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.113-120
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• 2014

In this paper, we examine Asymmetric Multi-Processing Environment to provide LDW service. Asymmetric Multi-Processing Environment consists of high-speed MCU to support rapid image processing and low-speed MCU for controlling with other ECU at the control domain. Also we designed rapid image process application and LDW application Software Component(SW-C) according to the development process rule of AUTOSAR. To communicate between two MCUs, timer based polling based IPC was designed. Also to communicate with other ECUs(Electronic Control Units), we designed CAN messages to provide alarm information and receiving CAN message to catch the Turn signal. We confirm the possibility of the various ADAS development using an Asymmetric Multi-Processing Environment and AUTOSAR platform. We also expect providing ISO 26262 functional safety.