• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.574-580
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• 2016

In this paper, we will introduce the system that can control multiple vehicles on the road through Single Board Computers and V2I (Vehicle-To-Infrastructure). Also, we will propose the group evasive maneuver decision algorithm, which plays a critical role in deciding whether the vehicles in the system have to conduct evasive maneuvers to avoid obstacles on the road. In order to test this system, we have utilized Wi-Fi and TCP/IP for establishing the communication between multiple vehicles and the relay server, and observed their driving states on the road with obstacles. During the experiments, we have discovered that our original decision algorithm possesses high failure rate when there is frequency interference in ISM (Industrial Scientific Medical) band. In order to reduce this failure rate, we have implemented the data transition detector. This paper will focus on how the use of data transition detector can affect the reliability of the system under the frequency interference of ISM band. If this technology is improved and applied in the field, we will effectively deal with such dangerous situations as multiple collision accidents through vehicle-to-vehicle communication or vehicle-to-infrastructure communication. Furthermore, this can be applied to the autonomous driving technologies. This can be used as the reference data for the development of the similar system.

• Journal of Drive and Control
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• v.17 no.1
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• pp.27-36
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• 2020

The aim of this study is to design a simulation model for an electric All-Wheel-Drive (AWD) tractor to evaluate the performance of the selected component and agricultural work ability. The electric AWD tractor consists of four motors independently for each drive wheel, and each motor is combined with an engine generator, a battery pack, and reducers. The torque data of a 78 kW-class tractor was measured during plow tillage and driving operation to develop a workload cycle. A simulation model was developed by using commercial software, Simulation X, and it used the workload as the simulation condition. As a result of simulation analysis, the drive system, including an electric motor and reducers, was able to cope with high load during plow tillage. The SOC (State of Charge) level was influenced by the output power of the motor, and it was maintained in the range of 50~80%. The fuel consumed by the engine was about 18.23 L during working on a total of 8 fields. The electric AWD tractor was able to perform agricultural work for about 7 hours. In the future study, the electric AWD tractor will be developed reflecting the simulation condition. Research on the comparison between the simulation model and the electric AWD tractor should be performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.842-849
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• 2022

With the development of deep learning technology, there are many cases of using DNNs in embedded systems such as unmanned vehicles, drones, and robotics. Typically, in the case of an autonomous driving system, it is crucial to run several DNNs which have high accuracy results and large computation amount at the same time. However, running multiple DNNs simultaneously in an embedded system with relatively low performance increases the time required for the inference. This phenomenon may cause a problem of performing an abnormal function because the operation according to the inference result is not performed in time. To solve this problem, the solution proposed in this paper first reduces the computation by applying the Tucker decomposition to DNN models with big computation amount, and then, make DNN models run in parallel as much as possible in the unit of hidden layer inside the GPU. The experimental result shows that the DNN inference time decreases by up to 75.6% compared to the case before applying the proposed technique.

• Journal of Auto-vehicle Safety Association
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• v.9 no.1
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• pp.6-12
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• 2017

Regulation for the testing and operation of automated vehicles on public roadways has been recently developed all over the world. For example, the licensing standards and the evaluation technology for automated vehicles have been proposed in California, Nevada and EU. But specific safety evaluation scenarios for automated vehicles have not been proposed yet. This paper presents safety evaluation scenarios for extraordinary service permission of automated vehicles on highways. A total of seven scenarios are selected in consideration of safety priority and real traffic situation. Six scenarios are relevant with lane keeping and one scenario is relevant with lane change. All scenarios are developed based on existing ADAS evaluation scenarios and repeated simulation of automated vehicle algorithm. Safety evaluation factors as well as scenarios are developed. The safety factors are based on existing ADAS ISO requirements, ADAS safety factors and current traffic regulations. For the scenarios, a hunter vehicle is needed in addition to automated vehicle evaluated. The hunter vehicle performs multiple roles like preceding vehicle, cut-in vehicle and so on. The hunter vehicle is also automated vehicle equipped with high performance GPS, radar and Lidar. All the scenarios can be implemented by driving a lap on a KATRI ITS test track. These scenarios and safety evaluation factors are investigated via both a computer simulation and an experimental vehicle test on the test track. The experimental vehicle test was conducted with two automated vehicles, which are the evaluated vehicle and the hunter vehicle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• Clean Technology
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• v.28 no.3
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• pp.227-231
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• 2022

The demand for high-voltage power devices is rising in various industries, but especially in the transportation industry due to autonomous driving and electric vehicles. IGBT module parts of 3.3 kV or more are used in the power propulsion control device of electric vehicles, and the procurement of these parts for new construction and maintenance is increasing every year. In addition, research to optimize high-voltage IGBT parts is urgently required to overcome their very high technology entry barrier. For the development of high-voltage IGBT devices over 3.3 kV, the resistivity range setting of the wafer and the optimal conditions for major unit processes are important variables. Among the manufacturing processes to secure the optimal junction depth, the optimization of the diffusion process, which is one step of the unit process, was examined. In the diffusion process, the type of gas injected, the injection time, and the injection temperature are the main variables. In this study, the range of wafer resistance (Ω cm) was set for the development of high voltage IGBT devices through unit process simulation. Additionally, the well drive in (WDR) condition optimization of the diffusion process according to temperature was studied. The junction depth was 7.4 to7.5 ㎛ for a ring pattern width of 23.5 to25.87 ㎛, which can be optimized for supporting 3.3 kV high voltage power devices.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.149-163
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• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.18-25
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• 2020

With the development of water internet technology, data communication between objects is expanding. Research related to data communication technology between vehicles that incorporates related technologies into vehicles has been actively conducted. For data communication between mobile terminals, data stability, reliability, and real-time performance must be guaranteed. The 5 GHz Wi-Fi band, which is advantageous in bandwidth, communications speed, and wireless saturation of the wireless network, was selected as the data communications network between vehicles. This study analyzes how to design and implement a 5 GHz Wi-Fi network in a vehicle network. Considering the characteristics of the mobile communication terminal device, a continuous variable communications structure is proposed to enable high-speed data switching. We simplify the access point access procedure to reduce the latency between wireless terminals. By limiting the Transmission Control Protocol Internet Protocol (TCP/IP)-based Dynamic Host Configuration Protocol (DHCP) server function and implementing it in a broadcast transmission protocol method, communication delay between terminal devices is improved. Compared to the general commercial Wi-Fi communication method, the connection operation and response speed have been improved by five seconds or more. Utilizing this method can be applied to various types of event data communication between vehicles. It can also be extended to wireless data-based intelligent road networks and systems for autonomous driving.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.63-72
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• 2019

As a sub-concept of corporate or organization governance, business governance and IT governance have become major research topics in academia. However, despite the importance of process as a construct for mediating the domain between business and information technology, research on process governance is relatively inadequate. Process Governance focuses on activities that link business strategy with IT system implementation and explains the creation of corporate core values. The researcher studied the basic conceptual governance models of political science, sociology, public administration, and classified governance styles into six categories. The researcher focused on the series of metamodels. For examples, the traditional Strategy Alignment Model(SAM) by Henderson and Venkatraman which is replaced by the neo-SAM model, organizational governance network model, sequential organization governance model, organization governance meta model, process governance CUBE model, COSO and process governance CUBE comparison model, and finally Process Governance Framework and etc. The Major difference between SAM and neo-SAM model is Process Governance domain inserted between Business Governance and IT Governance. Among several metamodels, Process Governance framework, the core conceptual model consists of four activity dimensions: strategic aligning, human empowering, competency enhancing, and autonomous organizing. The researcher designed five variables for each activity dimensions, totally twenty variables. Besides four activity dimensions, there are six driving forces for Process Governance cycle: De-normalizing power, micro-power, vitalizing power, self-organizing power, normalizing power and sense-making. With four activity dimensions and six driving powers, an organization can maintain the flexibility of process governance cycle to cope with internal and external environmental changes. This study aims to propose the Process Governance competency model and Process Governance variables. The situation of the industry is changing from the function-oriented organization management to the process-oriented perspective. Process Governance framework proposed by the researcher will be the contextual reference models for the further diffusion of the research on Process Governance domain and the operational definition for the development of Process Governance measurement tools in detail.