• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.255-261
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• 2010

The evaluation regarding a transportation policy by an evaluation volition viewpoint there is a difference. Consequently the insurgent analysis which is simple compared to against the evaluation object it was accurate, the analysis which leads the order anger probably is necessary. The research which it sees for the evaluation regarding the transportation policy of the metropolis divided in road being understood, public transportation, parking and pedestrian environment, wide area transportation and transportation information and transportation field whole. And against these field it tried the ALSCAL method and MDPREF method which is a Multidimensional Scale method and it analyzed. The regression analysis result for a dimensional analysis ALSCAL method the case of the transportation policy star improvement degree which it follows in introduction presence of intelligence transportation system and MDPREF method it confronted to the transportation policy star improvement degree which it follows in expansion to construction of specific function appeared with the fact that it is the tendency probably. And the evaluation object and evaluation in the object which will cut the positioning one result was each divided in 4 group. And two methods all it was visible a similar tendency. The ALSCAL method currently transportation system construction degree condition in base and, the MDPREF method currently improvement degree of the transportation policy which it follows in traffic system construction appeared with the fact that it is desirable to establish a hereafter traffic policy in base.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.173-183
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• 2020

In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2793-2800
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• 2011

The purpose of this research is to develop and optimize a lane departure warning application based on a smartphone which can be applicable as a new platform for various mobile information applications. Recently, a lane detection warning system which is a representative application among safe driving assistant solutions is being commercialized. Due to the necessity of powerful embedded hardware platform and its price, its market is still not growing. In this research, it is proposed to develop and optimize a lane departure warning application on iPhone 3GS. OpenCV is used for efficient image processing, and for lane detection a heuristic algorithm based on Hough Transform is proposed. The application was developed under Macintosh PC platform with Xcode 3.2.4 development tools, downloaded to the iPhone and has been tested on the real paved road. The experimental result has shown that the detection ratio of the straight lane was over 90% and the processing speed was 1.52fps. For the enhancement of the speed, a few optimization methods were introduced and the fastest speed was 3.84fps. Through the improvement of lane detection algorithm, additional optimization works and the adoption of a new powerful platform, it will be successfully commercialized on smartphone application market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2942-2950
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• 2010

Car black box helps to investigate the cause of accident by recording time, position and videos as well as shock information. In addition, the car black box need a function to support safe driving for preventing accident. The representative driving support function is a lane departure warning. In order to implement the function, it is necessary to carry out the image processing to detect the lane first. The image processing algorithm requires computational burden to handle so much data and complicated structure of algorithm. This paper describes the efficient image processing algorithm with relatively low amount of computation for car black box embedded platform to detect lanes from the real-time lane image.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.53-62
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• 2003

This paper demonstrates the in-vehicle dilemma zone warning system (DZWS) project developed as a part of the Driver Advisory and Collision Warning System in Automated Vehicle and Highway System (AVHS). The DZWS project, one of the Korea national ITS projects in 2000 develops the in-vehicle warning device to support drivers' decision making on whether to stop or to proceed to clear the intersection prior to the onset of yellow signal for avoiding the high risk of collision at signalized intersections through the dedicated short range communication (DSRC). This paper explores the design of optimal communication systems between roadway and vehicles, the operational and functional concepts of dilemma zone warning system based on appropriate approach speeds, and the system integration for field test at two sites of signalized intersections. Findings from the system integration indicated that the system would be implemented in eliminating the dilemma zone relative to approach speeds and in reducing red light violations and intersection collisions through the in-vehicle warning device at signalized intersection.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.17-27
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• 2012

This study provides development information on Omni-Wheel Drive Rider Robot, futuristic electric scooters, with autonomous driving systems that are used for people including the disabled and senior. Also, it is meaningful in suggesting alternatives to replace motorized wheelchairs or electric scooters for the future. Prior to development of Omni-Wheel Drive Rider Robot with autonomous driving systems, it surveyed 49 people, including 18 people who own electric scooters and 31 senior people who have not. The summary of the survey is as follows. First, inconveniences during riding and exiting and short mileage due and safety driving to problems of recharging batteries are the most urgent task. For these problems, the study shows that charging time of batteries, mileage, armrests, footrests, angle of a seat are the primary considerations. Second, drivers prefer joystick over steering wheels because of convenience in one-handed driving against dangers from footrest and carriageways sloping roads, paving blocks. One-handed driving can reduce driving fatigues with automatic stop systems. Moreover, the study suggests many design factors related to navigation systems, obstacle avoidance systems, omni-wheels, automatic cover-opening systems in rainy.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.55-61
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• 2009

In order to observe the impact of a type of vehicles for traffic flows and pavement, vehicle classifications is conducted. Korean Ministry of Land, Transport and Maritime Affairs provides 12-type vehicle classifications on National expressways, National highways, and Provincial roads. Current AVC (Automatic Vehicle Classification) devices decide vehicle types comparing measurements of vehicle lengths, wheelbases, overhangs etc. to a reference table including those of all types of models. This study developed an algorithm for macroscopic vehicle classification which is less sensitive to tuning sensors and updating the reference table. For those characteristics, trend lines in vehicle lengths and wheelbases are employed. To assess the algorithm developed, vehicle lengths and wheelbases were collected from an AVC device. In this experiment, this algorithm showed the accuracy of 88.2 % compared to true values obtained from video replaying. Our efforts in this study are expected to contribute to developing devices for macroscopic vehicle classification.

• Management & Information Systems Review
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• v.4
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• pp.257-284
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• 2000

According as the drivers increase who have their cars, the comprehensive studies on the automobile for the traffic safety have been raised as the important problems. Visual Recognition System for radio-controled driving is a part of the sensor processor of Unmanned Autonomous Vehicle System. When a driver drives his car on an unknown highway or general road, it produces a model from the successively inputted road traffic information. The suggested Recognition System of the Road Traffic Safety Information Board is to recognize and distinguish automatically a Road Traffic Safety Information Board as one of road traffic information. The whole processes of Recognition System of the Road Traffic Safety Information Board suggested in this study are as follows. We took the photographs of Road Traffic Safety Information Board with a digital camera in order to get an image and normalize bitmap image file with a size of $200{\times}200$ byte with Photo Shop 5.0. The existing True Color is made up the color data of sixteen million kinds. We changed it with 256 Color, because it has large capacity, and spend much time on calculating. We have practiced works of 30 times with erosion and dilation algorithm to remove unnecessary images. We drawing out original image with the Region Splitting Technique as a kind of segmentation. We made three kinds of grouping(Attention Information Board, Prohibit Information Board, and Introduction Information Board) by RYB( Red, Yellow, Blue) color segmentation. We minimized the image size of board, direction, and the influence of rounding. We also minimized the Influence according to position. and the brightness of light and darkness with Eigen Vector and Eigen Value. The data sampling this feature value appeared after building the learning Code Book Database. The suggested Recognition System of the Road Traffic Safety Information Board firstly distinguished three kinds of groups in the database of learning Code Book, and suggested in order to recognize after comparing and judging the board want to recognize within the same group with Nearest Neighborhood Decision Making.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.13-24
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• 2008

Real-time traffic data are readily obtainable by traffic surveillance systems of intelligent transportation systems (ITS). Such data greatly support further applications in the field of traffic operations, planning, and safety. However, traffic data should be appropriately processed to fully exploit the benefits of data collection capability. Rather than developing individual data processing techniques, which is major concern of existing studies, this study proposes a novel methodology for evaluating data processing techniques in an integrated manner. Also, a tool for implementing the proposed methodology is developed. Users can extract useful and more reliable traffic data based upon their ultimate purpose of data usage by the evaluation tool developed in this study. Actual freeway traffic data are, as an example, fed into the evaluation tool, and results are discussed.