• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.99-107
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• 2016

PURPOSES : This study was initiated to estimate expressway traffic congestion costs by using Vehicle Detection System (VDS) data. METHODS : The overall methodology for estimating expressway traffic congestion costs is based on the methodology used in a study conducted by a study team from the Korea Transport Institute (KOTI). However, this study uses VDS data, including conzone speeds and volumes, instead of the volume delay function for estimating travel times. RESULTS : The expressway traffic congestion costs estimated in this study are generally lower than those observed in KOTI's method. The expressway lines that ranked highest for traffic congestion costs are the Seoul Ring Expressway, Gyeongbu Expressway, and the Youngdong Expressway. Those lines account for 64.54% of the entire expressway traffic congestion costs. In addition, this study estimates the daily traffic congestion costs. The traffic congestion cost on Saturdays is the highest. CONCLUSIONS : This study can be thought of as a new trial to estimate expressway traffic congestion costs by using actual traffic data collected from an entire expressway system in order to overcome the limitations of associated studies. In the future, the methodology for estimating traffic congestion cost is expected to be improved by utilizing associated big-data gathered from other ITS facilities and car navigation systems.

• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.89-95
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• 2022

A method for measuring the length and slope of a temporary structure using an unmanned aerial vehicle (UAV) and 3D modeling method is proposed. The actual length and slope of the vertical member of the specimen were measured and compared with the measured values obtained by the proposed method for the specimens with and without the vertical protection net installed. Based on the result of measuring the length of the temporary structure specimen using the UAV and 3D modeling method, the measured value showed an error of 0.87% when compared to the actual length in the specimen without the vertical protection net installed. In addition, the error of the slope was 0.63°. It was thought that the proposed method could be usable for the purpose of finding parts in wrong installation state on the temporary structure and informing the manager in charge. However, in the case of the specimen with the vertical protection net, the measurement showed a 1.46% error in length and 2.77° difference in slope. Therefore, if a vertical protection net is to be installed in a temporary structure, the measurement accuracy should be improved by utilizing an image processing method, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1166-1174
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• 2015

There were the attempts to prevent the spread of harmful materials of the agri-food through the record tracking of the products with the bar code, the partial information tracking of the agri-food storage and the delivery vehicle, or the control of the temperature by intuition. However, there were many problems in the attempts because of the insufficient information, the information distortion and the independent information network of each distribution company. As a result, it is difficult to prevent the spread over the life-cycle of the agri-food using the attempts. To solve the problems, we propose the mechanism mainly to do context awareness, predict, and track the harmful materials of agri-food using big data processing.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.17-24
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• 2018

This paper proposes data mining models relevant to the serial publication periods and mobile gamification likelihood of webtoon contents which were either serialized or completed in platform. The size of the cartoon industry including webtoon takes merely 1% of the total entertainment contents industry in Korea. However, the significance of webtoon business is rapidly growing because its intellectual property can be easily used as an effective OSMU (One Source Multi-Use) vehicle for multiple types of contents such as movie, drama, game, and character-related merchandising. We suggested a set of data mining classifiers that are deemed suitable to provide prediction models for serial publication periods and mobile gamification likelihood for the sake of webtoon contents. As a result, the balanced accuracies are respectively recorded as 85.0% and 59.0%, from the two models.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.14-22
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• 2021

A plan for the development of reliability-based ROK amphibious assault vehicles is proposed. By analyzing the development case of the U.S. EFV, considerations for the successful development of the next-generation Korea Forces amphibious assault vehicle are presented. If the vehicle reliability can be improved to the level of the fourth highest priority electric unit for power units, suspensions, decelerators, and body groups, which have the highest priority among fault frequency items, a system level MTBF of 36.4%↑ can be achieved, and the operational availability can be increased by 3.5%↑. The next-generation amphibious assault vehicles must fulfill certain operating and performance requirements, the underlying systems must be built, and sequencing of the hybrid engine and the modular concept should be considered. Along with big-data- and machine-learning-based failure prediction, machine maintenance based on augmented reality/virtual reality and remote maintenance should be used to improve the ability to maintain combat readiness and reduce lifecycle costs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2153-2159
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• 2013

In order to drive a vehicle safely, driver needs to check status of the car. Many moderns are having trouble to spare time to visit auto mechanic and have car mechanics to check their car other than their office hours. If the car status cannot be inspected regularly, it is likely to cause a big accident threatening the surroundings as well as driver's life. Inspection tool and system help driver to check their own vehicle status personally are required for preventing it. In this paper, it designed and realized system that records driving information based on changing data of vehicle (location and automotive internal data) and allows driver can check the vehicle status easily and further, driver can share the driving information with repair shop via the Internet to receive detailed inspection service for car status.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.247-258
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• 2017

Since 2016 when the regulations related to vehicle structure and device modification were drastically revised, the car tuning market has been growing rapidly. Particularly, many drivers are showing interest in changing the interior and exterior according to their preference, or improving the specifications of their cars by changing the engine and powertrain, among others. Also, as the initial engine settings such as horse power and torque of the vehicle are made for stable driving of the vehicle, it is possible to change the engine performance, via Engine Control Unit (ECU) mapping, to the driver's preference. However, traditionally, ECU mapping could be only performed by professional car engineers and the settings were also decided by them. Therefore, this study proposed a system that collects data related to the driver's driving habits for a certain period and sends them to a cloud server in order to analyze them and recommend ECU mapping values. The traditional mapping method only aimed to improve the car's performance and, therefore, if the changes were not compatible with the driver's driving habits, could cause problems such as incomplete combustion or low fuel efficiency. However, the proposed system allows drivers to set legally permitted ECU mapping based on analysis of their driving habits, and, therefore, different drivers can set it differently according to the vehicle specifications and driving habits. As a result, the system can optimize the car performance by improving output, fuel efficiency, etc. within the range that is legally permitted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1871-1879
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• 2008

A few years ago, The trains had little control equipment so the trains had little data transmission between control equipment. Recently, there is a lot of control equipment in a train as traction control, air conditioners and even internet access. for this reason, vehicle network must allow for the big amount of transmission data and must ensure the high reliability. In this paper we present monitering system for verify high reliability of data transmission of MVB of TCN which is an international standard of IEC 61375.