• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.96-108
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• 2017

The current collision warning and avoidance system(CWAS) is one of the representative Advanced Driver Assistance Systems (ADAS) that significantly contributes to improve the safety performance of a vehicle and mitigate the severity of an accident. However, current CWAS mainly have focused on preventing a forward collision in an uninterrupted flow, and the prevention performance near intersections and other various types of accident scenarios are not extensively studied. In this paper, the safety performance of Vision-Sensor (VS) and Radar-Sensor(RS) - based collision warning systems are evaluated near an intersection area with the data from Naturalistic Driving Study(NDS) of Second Strategic Highway Research Program(SHRP2). Based on the VS and RS data, we newly derived sixteen vehicle-to-vehicle accident scenarios near an intersection. Then, we evaluated the detection performance of VS and RS within the derived scenarios. The results showed that VS and RS can prevent an accident in limited situations due to their restrained field-of-view. With an accident prevention rate of 0.7, VS and RS can prevent an accident in five and four scenarios, respectively. For an efficient accident prevention, a different system that can detect vehicles'movement with longer range than VS and RS is required as well as an algorithm that can predict the future movement of other vehicles. In order to further improve the safety performance of CWAS near intersection areas, a communication-based collision warning system such as integration algorithm of data from infrastructure and in-vehicle sensor shall be developed.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.173-178
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• 2013

It is a concern that eco-driving vehicles, because their driving behavior differs from other vehicles due to e.g. e-start, may inhibit smooth traffic flow. Therefore, it is necessary to study the cooperative eco-driving done by a vehicle group, putting "vehicle-to-vehicle communication" and "road-to-vehicle communication" into perspective. Based on these factors, this study aimed to: 1) Analyze fuel consumption rates and driving behaviors of more than one vehicle following an Eco-Driving vehicle. 2) Examine the effect of information on the fuel consumption rate of the preceding vehicles on the following vehicles. As a result, the following findings were obtained: 1) By providing information to multiple following vehicles, the fuel consumption rate of the second vehicle was not lowered, while that of the third one was. 2) It is possible that, when information on fuel consumption of a preceding vehicle is provided to the following one, an inter-vehicular distance is shortened during deceleration to contribute to smooth traffic flow. From the above results, it is suggested that, when targeting a vehicle group, sharing the information on preceding vehicles is effective.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.253-263
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• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.171-180
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• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.190-211
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• 2022

This study investigated the effect of the shape and height of road signs on detection performance when detecting road signs with LiDAR, which is recognized as an essential sensor for autonomous vehicles. For the study, four types of road signs with the same area and material and different shapes were produced, and a road driving test was performed by installing a 32Ch rotating LiDAR on the upper part of the vehicle. As a result of comparing the shape of the point cloud and the NPC according to the shape of the road sign, It is expected that a distance of less than 40m is required to recognize the overall shape of a road sign using 32Ch LiDAR, and shapes such as triangles and rectangles are more advantageous than squares in securing the maximum point cloud from a long distance. As a result of the study according to the height of the road sign, At short distances (within 20m), if the height of the sign is raised to more than 2m, it deviates from the vertical viewing angle of the LiDAR and cannot express the complete point cloud shape. However, it showed a negligible effect compared to the near-field height change. These research results are expected to be utilized in the development of road facilities dedicated to LiDAR for the commercialization of autonomous cooperative driving technology.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.95-108
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• 2001

The provision of spatial data is a key infrastructural requirement for the promotion of economic growth, environmental quality, social progress, etc. 4S technology integrates 4 kinds of systems that process spatial data: GIS (Geographic Information System), GNSS (Global Navigation Satellite System), ITS (Intelligent Transport System), and SIIS (Spatial Imagery Information System). Spatial data processing field is expected to get synergy effect and overcomes development limit of individual unit technology via 4S technology. This paper discusses both the development of 4S-kernel technology and the construction of 4S-based framework, In the development of 4S kernel technology, we will concentrate on the following issues: the development of 4S base components for reciprocity integration among GIS, SIIS, GNSS and ITS technologies, the development of 4S-Mobile S/W and H/W, 4S-Van components, and national LBS technologies. And in the construction of 4S-based framework, we will especially concentrate on the ISP for overall 4S technologies, the international cooperative research center, and the guide model deduction for supervision and certification of 4S projects. Finally, we examine about how the construction of 4S-baed framework affects 4S industry.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.10
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• pp.899-905
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• 2016

Wireless access in vehicle environment (WAVE) communication is currently being researched as core wireless communication technologies for cooperative intelligent transport systems (C-ITS). WAVE consists of both vehicle to vehicle (V2V) communication, which refers to communication between vehicles, and vehicle to infrastructure (V2I) communication, which refers to the communication between vehicles and road-side stations. V2I has a longer communication range than V2V, and its communication range and reception rate are heavily influenced by various factors such as structures on the road, the density of vehicles, and topography. Therefore, domestic environments in which there are many non-lines of sight (NLOS), such as mountains and urban areas, require optimized communication channel modeling based on research of V2I propagation characteristics. In the present study, the received signal strength indicator (RSSI) was measured on both an experience road and a test road, and the large-scale characteristics of the WAVE communication were analyzed using the data collected to assess the propagation environment of the WAVE-based V2I that is actually implemented on highways. Based on the results of this analysis, this paper proposes a WAVE communication channel model for domestic public roads by deriving the parameters of a dual-slope logarithmic distance implementing a two-ray ground-reflection model.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.81-91
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• 2016

VANET is one of the most developed technologies many people have considered a technology for the next generation. It basically utilizes the wireless technology and it can be used for measuring the speed of the vehicle, the location and even traffic control. With sharing those information, VANET can offer Cooperative ITS which can make a solution for a variety of traffic issues. In this way, safety for drivers, efficiency and mobility can be increased with VANET but data between vehicles or between vehicle and infrastructure are included with private information. Therefore alternatives are necessary to secure privacy. If there is no alternative for privacy, it can not only cause some problems about identification information but also it allows attackers to get location tracking and makes a target. Besides, people's lives or property can be dangerous because of sending wrong information or forgery. In addition to this, it is possible to be information stealing by attacker's impersonation or private information exposure through eavesdropping in communication environment. Therefore, in this paper we propose Privacy Assurance Architecture for VANET to ensure privacy from these threats.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.