• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.417-429
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• 2010

Though background subtraction has been widely studied for last decades, it is still a poorly solved problem especially when it meets real environments. In this paper, we first address some common problems for background subtraction that occur in real environments and then those problems are resolved by improving an existing GMM-based background modeling method. First, to achieve low computations, fixed point operations are used. Because background model usually does not require high precision of variables, we can reduce the computation time while maintaining its accuracy by adopting fixed point operations rather than floating point operations. Secondly, to avoid erroneous backgrounds that are induced by high pedestrian traffic, static levels of pixels are examined using shot-time statistics of pixel history. By using a lower learning rate for non-static pixels, we can preserve valid backgrounds even for busy scenes where foregrounds dominate. Finally, to adapt rapid illumination changes, we estimated the intensity change between two consecutive frames as a linear transform and compensated learned background models according to the estimated transform. By applying the fixed point operation to existing GMM-based method, it was able to reduce the computation time to about 30% of the original processing time. Also, experiments on a real video with high pedestrian traffic showed that our proposed method improves the previous background modeling methods by 20% in detection rate and 5~10% in false alarm rate.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.657-666
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• 2001

In this paper, it is proposed the management items for voice traffic using CDRs so that global carriers can treat and manage the voice traffic for a customer, and defined computational expressions to produce the management items. From them, we have designed the management system, which is composed of web interface module, analysis module, data collection module and database management module, and have improved the availability and convenience of the system using web technologies. In addition, we have tested these items using CDRs in real environments that are collected by the global carrier in order to verify their validity. It is expected that the proposed web based voice traffic management system provide a global carrier with network information collection, fault detection/trouble-shooting and high quality of service through analyzing the characteristics of subscribers.

• Proceedings of KOSOMES biannual meeting
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• 2005.05a
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• pp.37-43
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• 2005

Recently, many ships such as fishing boats, cargo ships, high speed ferry boats are visiting Mokpo harbor. In particular, many marine accidents rave been occurred at this area because of the narrow channel, a thick fog, the existing of the shallow waters etc. However there is no suitable ships' routeing system which takes account of today's traffic situations in this area. This study aims at the settling of hazardous factors to mitigate the danger to vessels in mokpo harbor and to secure the safety qf maritime environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.4
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• pp.375-381
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• 2013

To assess the risk of marine traffic environments, with high confidential level, the risk factors comprising it should be identified and the risk acceptance criteria should be also provided. Furthermore, the relative importance of each risk factor(the weight of each risk factor on total risk) should be analyzed because the risk is expressed as the sum of risk factors comprising it. The twenty kinds of risk factors and its assessment criteria were suggested for the domestic marine traffic environments by an examination of the existing risk assessment models on the previous studies. The relative importance of each risk factor was also analyzed through the questionnaire using analytic hierarchy process by the marine traffic experts on the same studies. Based on these previous studies, the risk was evaluated at the port of Mokpo and its approaches on this study. The port of Mokpo and its approaches were divided into four sectors for the comparative evaluation, the result of the comparative evaluation on four sectors showed that the risk of the Jeongdeung-hae passage is the highest due to higher risk level of some risk factors(water movements, complexities, tug boats, pilotage, VTS) than the other sectors. The result of this evaluation is in accord with the analysis results of the other studies using various qualitative or quantitative risk analysis methods at the same sea areas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.281-288
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• 2024

The sixth generation(6G) wireless communication technology is advancing toward ultra-high speed, ultra-high bandwidth, and hyper-connectivity. With the development of communication technologies, the formation of a hyper-connected society is rapidly accelerating, expanding from the IoT(Internet of Things) to the IoE(Internet of Everything). However, at the same time, security threats targeting IoT devices have become widespread, and there are concerns about security incidents such as unauthorized access and information leakage. As a result, the need for security-enhancing solutions is increasing. In this paper, we implement an autoencoder-based anomaly detection model utilizing real-time collected network traffics in respond to IoT security threats. Considering the difficulty of capturing IoT device traffic data for each attack in real IoT environments, we use an unsupervised learning-based autoencoder and implement 6 different autoencoder models based on the use of noise in the training data and the dimensions of the latent space. By comparing the model performance through experiments, we provide a performance evaluation of the anomaly detection model for detecting abnormal network traffic.

• Journal of KIISE:Information Networking
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• v.31 no.6
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• pp.573-581
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• 2004

Recently, the rapid growth of Internet technology and the deployment of high speed networks make many kinds of multimedia services possible. Preexisting multimedia services are designed based on the client/server model which has the problems such as the network failure and the low speed communication due to the high load on the central server. In order to solve these problems, peer-to-peer networks are introduced and expanded through Internet environments. In this paper, we propose a pure peer-to-peer network based resource discovery mechanism for multimedia services. In the proposed scheme, each host maintains the location information of resources which are recently requested by other hosts as well as that oi the replicas of local resources. The proposed scheme has the faster response time and incurs the smaller traffic than the preexisting discovery schemes in pure peer-to-peer network environments. Also, by decentralizing the location information and differentiating the reply path, our proposed scheme can solve the search result loss problem that occurs when the network is unsettled.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1166-1178
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• 2016

In Internet of Things (IoT) environments, billions of interconnected devices and multimedia sensors generate a huge amount of multimedia traffic. Since the environment are in general deployed as a server-centric architecture wireless sensor networks could be bottlenecks between IoT gateways and IoT devices. The bottleneck causes high power consumption of the device and triggers very heavy network overload by transmission of sensing data. The deterioration could decrease the quality of multimedia streaming service due to delay, loss, and waste of device power. Thus, in this paper, we propose a context-based adaptive multimedia streaming scheme to support enhanced QoS and low power consumption in IoT environments. The goal of the scheme is to increase quality score per voltage of the streaming service, given an adaptation algorithm with context that are classified network and hardware such as throughput, RTT, and CPU usage. From the both context, the quality score per voltage is used in the comparison of a only network context-based adaptive multimedia streaming scheme, a fixed multimedia streaming and our scheme. As a result, we achieves a high improvement that means the quality score per voltage is increased up to about 4, especially in case of resolution change.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.299-305
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• 2019

In ISO MPEG, MPEG-H has been standardized to smoothly deliver huge volume of ultra-high resolution videos over heterogeneous network environments for the consumers. In the MPEG-H standard, MMT(MPEG Media Transport) protocol is the next generation MPEG media transport technology to provide hybrid media delivery over heterogeneous environments. It is important to sustain accurate media synchronization to provide ultra-high resolution video services over heterogeneous network environments. In this paper, we propose and verify an in-band media synchronization scheme to circumvent the problem of additional session setup and excessive traffic problems of the conventional out-of-band media synchronization supported by the MMT technology.