• The Korean Journal of Air & Space Law and Policy
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• v.15
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• pp.35-39
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• 2002

• The Korean Journal of Air & Space Law and Policy
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• v.1
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• pp.9-46
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• 1989

• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.107-107
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• 2001

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.147-156
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• 2009

The aim of this study is to propose an integrated press system design for traffic information service by multi-connecting traffic information services which are now being serviced by each different requirements for the press service and by providing advanced traveler information service which organically user oriented design such as traffic broadcast, news, journal, semantic web and also related traffic ontology as well as road traffic information. For the objective, the status of domestic and foreign traffic information supply system was analyzed and then the requirements by media were reviewed. Then, by analyzing the system implementation method and the implementation system the method of implementing such the system was suggested. The design method suggested in this study enabled the information users to utilize a variety of traffic information through intervening between the necessary and sufficient conditions of information users and information suppliers. Throughout the result of this study, for the users who used the integrated transport, the efficient space movement and the economic using value was improved. Providing the traffic information through the press media will become useful information to road drivels, and it is effected that the traffic volume will be dispersed and the traffic jam will be relieved owing to the supply of traffic information to the press.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.29-34
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• 2015

Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.298-305
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• 2019

The demand for the revitalization of marine tourism in Busan North Port is increasing due to changes in functions such as an increase in harbor traffic volume and the expansion of marine leisure space in Busan. As a result, Busan City plans to set a phased alleviation target for prohibition of cruise ship operations, and to lift the prohibition of excursion ship operations in North Port following the cancellation of the prohibition of excursion ship operations in South Port in 2017. The purpose of this study is to evaluate the risk of excursion ship operations in Busan North Port by applying the marine traffic assessment index and to examine the possibility of excursion ship operations. For this purpose, port status, marine accidents, and traffic flow of Busan North Port were investigated. In addition, marine traffic assessment indexes, such as traffic congestion, risk based on an ES Model, and IWRAP MkII, a maritime risk assessment tool, were used to assess the risk and possibility of excursion ship operations in Busan North Port. This study can be used as basic data for analyzing the risk factors that may occur when excursion ships are operated in Busan North Port and to define how excursion ships should operate, with related safety measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.75-82
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• 2021

The number of traffic accidents is about 230,000, and due to non-recurring congestion and high driving speed, the number of deaths per traffic accident on freeways is more than twice compared to other roads. Currently, traffic information is provided based on nodes and links using the centerline of the road, but it does not provide detailed speed information. Recently, installing sensors for vehicles to monitor obstacles and measure location is becoming common not only for autonomous vehicles but also for ordinary vehicles as well. The analysis using large-capacity location-based data from such sensors enables real time service according to processing speed. This study presents an mapping method for individual vehicle data analysis based on space. The processing speed of large-capacity data was increased by using method which applied a quaternary notation basis partition method that splits into two directions of longitude and latitude respectively. As the space partition was processed, the average speed was similar, but the speed standard deviation gradually decreased, and decrease range became smaller after 9th partition.

• Wind and Structures
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• v.27 no.4
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• pp.255-267
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• 2018

This paper investigated the wind-snow flow around the bogie region of a high-speed train under crosswinds using a coupled numerical method of the unsteady Realizable $k-{\varepsilon}$ turbulence model and discrete phase model (DPM). The flow features around the bogie region were discussed and the influence of bogie fairing height on the snow accumulation on the bogie was also analyzed. Here the high-speed train was running at a speed of 200 km/h in a natural environment with the crosswind speed of 15 m/s. The mesh resolution and methodology for CFD analysis were validated against wind tunnel experiments. The results show that large negative pressure occurs locally on the bottom of wheels, electric motors, gear covers, while the positive pressure occurs locally on those windward surfaces. The airflow travels through the complex bogie and flows towards the rear bogie plate, causing a backflow in the upper space of the bogie region. The snow particles mainly accumulate on the wheels, electric motors, windward sides of gear covers, side fairings and back plate of the bogie. Longer side fairings increase the snow accumulation on the bogie, especially on the back plate, side fairings and brake clamps. However, the fairing height shows little impact on snow accumulation on the upper region of the bogie. Compared to short side fairings, a full length side fairing model contributes to more than two times of snow accumulation on the brake clamps, and more than 20% on the whole bogie.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of Communications and Networks
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• v.10 no.3
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• pp.287-296
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• 2008

The IEEE 802.11 wireless standard uses the carrier sense multiple access with collision avoidance (CSMA/CA) as its MAC protocol (during the distributed coordination function period). This protocol is an adaptation of the CSMA/CD of the wired networks. CSMA/CA mechanism cannot guarantee quality of service (QoS) required by the application because orits random access method. In this study, we propose a new MAC protocol that considers different types of traffic (e.g., voice and data) and for each traffic type different priority levels are assigned. To improve the QoS of IEEE 802.11 MAC protocols over a multi-channel CSMA/CA, we have developed a new admission policy for both voice and data traffics. This protocol can be performed in direct sequence spread spectrum (DSSS) or frequency hopping spread spectrum (FHSS). For voice traffic we reserve a channel, while for data traffic the access is random using a CSMA/CA mechanism, and in this case a selective reject and push-out mechanism is added to meet the quality of service required by data traffic. To study the performance of the proposed protocol and to show the benefits of our design, a mathematical model is built based on Markov chains. The system could be represented by a Markov chain which is difficult to solve as the state-space is too large. This is due to the resource management and user mobility. Thus, we propose to build an aggregated Markov chain with a smaller state-space that allows performance measures to be computed easily. We have used stochastic comparisons of Markov chains to prove that the proposed access protocol (with selective reject and push-out mechanisms) gives less loss rates of high priority connections (data and voices) than the traditional one (without admission policy and selective reject and push-out mechanisms). We give numerical results to confirm mathematical proofs.