• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.208-218
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• 2017

This study aims to develop the Vehicle Local Dynamic Map (V-LDM) and demonstrate its performance for providing dynamic map data efficiently to the vehicle control module. Firstly, the concept of the in-vehicle LDM has been established and then the system has been carefully designed according to the international standards. The high-precision digital map embedded in LDM has been designed to incorporate the lane-level information of road network, and the Dynamic Map protocol (DM protocol) which is a message protocol including the road data with dynamic traffic event data has been defined. The performance test of the proposed system has been conducted in the uninterrupted road section of Kyungbu expressway, showing that both of the data size and the elapsed time to finish the process are almost linearly proportional to the length of target road. Finally, it is recommended that the length of target road for DM protocol be less than 250m.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.122-134
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• 2020

To improve traffic congestion, reduce fuel consumption, and improve the stability of truck operations, truck platooning, in which several trucks are organized in a single platoon, is being actively researched globally. Compared to the operation of a single truck, the operation of a truck platoon requires more caution before the actual operation because an accident of one vehicle in the platoon can lead to an accident with all the vehicles in the platoon. Therefore, this study examined the types of trucks and cargo suitable for truck platooning to prevent safety accidents. The review showed that a closed-van-type truck is appropriate for truck platooning to prevent falling objects during driving. In the case of cargo types, it is necessary to exclude liquids and dangerous goods defined in related laws from truck platooning.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.1-17
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• 2021

Identifying the exact train and the type of train boarded by passengers is practically cumbersome. Previous studies identified the trains boarded by each passenger by matching the Automated Fare Collection (AFC) data and the train schedule diagram. However, this approach has been shown to be inefficient as the exact train boarded by a considerable number of passengers cannot be accurately determined. In this study, we demonstrate that the AFC data - diagram matching technique could not estimate 28% of the train type selected by passengers using the Seoul Metro line no.9. To obtain more accurate results, this paper developed a two-step method for estimating the train type boarded by passengers by applying the AFC data - diagram matching method followed by a mixture distribution analysis. As a result of the analysis, we derived reasonable express train use/non-use passenger classification points based on 298 origin-destination pairs that satisfied the verification criteria of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.114-128
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• 2019

Recently, the interest in the safety of autonomous vehicles has globally been increasing. Also, there is controversy over the reliability and safety about autonomous vehicle. In Korea, the K-City which is a test-bed for testing autonomous vehicles has been constructing. There is a need for test scenarios for autonomous vehicle test in terms of safety. The purpose of this study is to develop the evaluation scenario for autonomous vehicle at community roads in K-City by using crash data collected by the Korea National Police Agency and a text-mining technique. As a result, 24 scenarios were developed in order to test autonomous vehicle in community roads. Finally, the logical and concrete scenario forms were derived based on the Pegasus 5-layer format.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.624-627
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• 2014

In vehicular network, the basic goal is to provide vehicle safety service and commercial service such as ITS(Intelligent Transportation System) or video, etc on the road. And most research concentrated on transportation of safety message in congestion situation. It is important to allocate channel for safety message in congestion situation, but providing suitable service is also important problem in vehicular network. For this reason, IEEE 1609.4 allocate 4 multiple service channels (SCHs) for non-safety data transfer. But, in congestion situation with many vehicles, the contention for channel acquisition between services becomes more severe. So services are provided improperly because of lack of service channel. This paper suggests dynamic channel allocation algorithm. The proposed algorithm is that RSU(RaodSide Unit) maintain and manage the information about service and status of channels. On based of the SJF(Shortest Job First) scheduling using those information, RSU selects the most appropriate channel among the 4 SCHs allocated by IEEE 1609.4 in network congestion situation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.192-202
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• 2021

In the past, various studies have been conducted on safety facility installation standards and road safety indices. But there are limitations in applying them to the field, such as using many survey items and variables that are difficult to use. Therefore, this study attempted to develop road safety judgment indicators considering the applicability of the research results and to prepare criteria for installing safety facilities. As part of the study, data of related systems were reviewed, and the use of variables already in use was figured out. Furthermore, the road safety judgment indicators reflecting traffic, road, and accident factors were developed through correlation and factor analysis. Later, the criteria score for determining the installation of safety facilities was derived through cluster analysis. The analyses suggested, that the installation judgment criterion score at the intersection was lower than that of the single road(crosswalk), and the road risk at the intersection was higher.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.1-17
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• 2022

Accurate analysis of the causes of metro rail traffic congestion provides a means of addressing issues arising from metro rail traffic congestion in metropolitan areas. Currently, congestion analysis based on counting, weight detection, CCTVs, and mobile Wi-Fi is limited by poor accuracies or because studies have been restricted to single routes and trains. In this study, a train congestion analysis model was used that includes the transfer and multi-path behavior of metro passengers and train operation plans for metropolitan urban railroads. Analysis accuracy was improved by considering traffic patterns in which passengers must wait for next trains due to overcrowding. The model updates train crowding levels every 10 minutes, provides information to potential passengers, and thus, is expected to increase the social benefits provided by the Seoul metropolitan subway

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.250-265
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• 2022

Positive effects such as significantly reducing traffic accidents caused by human error can be expected by the introduction of Automated vehicles (AV). However, as new traffic safety issues are expected to occur in the future due to errors in H/W or S/W of autonomous vehicles and lack of its function, it is necessary to establish a scenario to evaluate the driving safety of AV. Therefore, in this study, functional scenario was developed to evaluate the driving safety of AV based on traffic accident data of the National Police Agency. Using the GIS program, QGIS, traffic accident data that occurred in the toll gate and ramp sections of expressway were extracted and accident summary items were checked to classify the types of accident. In addition, based on the results of accident type classification, functional scenario were developed that contains various dangerous situations in the tollgate and ramp sections.