• 제목/요약/키워드: Driving performance

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Road Extraction from Images Using Semantic Segmentation Algorithm (영상 기반 Semantic Segmentation 알고리즘을 이용한 도로 추출)

  • Oh, Haeng Yeol;Jeon, Seung Bae;Kim, Geon;Jeong, Myeong-Hun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.3
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    • pp.239-247
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    • 2022
  • Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

A LiDAR-based Visual Sensor System for Automatic Mooring of a Ship (선박 자동계류를 위한 LiDAR기반 시각센서 시스템 개발)

  • Kim, Jin-Man;Nam, Taek-Kun;Kim, Heon-Hui
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.6
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    • pp.1036-1043
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    • 2022
  • This paper discusses about the development of a visual sensor that can be installed in an automatic mooring device to detect the berthing condition of a vessel. Despite controlling the ship's speed and confirming its location to prevent accidents while berthing a vessel, ship collision occurs at the pier every year, causing great economic and environmental damage. Therefore, it is important to develop a visual system that can quickly obtain the information on the speed and location of the vessel to ensure safety of the berthing vessel. In this study, a visual sensor was developed to observe a ship through an image while berthing, and to properly check the ship's status according to the surrounding environment. To obtain the adequacy of the visual sensor to be developed, the sensor characteristics were analyzed in terms of information provided from the existing sensors, that is, detection range, real-timeness, accuracy, and precision. Based on these analysis data, we developed a 3D visual module that can acquire information on objects in real time by conducting conceptual designs of LiDAR (Light Detection And Ranging) type 3D visual system, driving mechanism, and position and force controller for motion tilting system. Finally, performance evaluation of the control system and scan speed test were executed, and the effectiveness of the developed system was confirmed through experiments.

A Study on Cell-Broadcasting Based Security Authentication System and Business Models (셀 브로드캐스팅 보안 인증시스템 및 비즈니스 모델에 관한 연구)

  • Choi, Jeong-Moon;Lee, Jungwoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.325-333
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    • 2021
  • With the rapidly changing era of the fourth industrial revolution, the utilization of IT technology is increasing. In addition, the demand for security authentication is increasing as shared services or IoT technologies are being developed as new business models. Security authentication is becoming increasingly important for all intelligent devices such as self-driving cars. However, most location-based security authentication technologies are being developed mainly with technologies that utilize server proximity or satellite location tracking, which limits the scope of their physical use. Location-based security authentication technology has recently been developed as a complementary replacement technology. In this study, we introduce location-based security authentication technology using cell broadcasting technology, which has a wider range of applications and is more convenient and business-friendly than existing location-based security authentication technologies. We also introduced application cases and business models related to this. In addition to the current status of technology development, we analyzed current changes in business models being employed. Based on our analysis results, this study draws the implication that technology diversification is necessary to improve the performance of innovative technologies. It is meaningful that it has found and studied advanced technologies other than existing location authentication methods and systems.

The Effects of Technology Commercialization Capability and Competitive Strategy of Venture Companies on Growth Prospects: Focused on Mediating Effect of Business Model Innovation (벤처기업의 기술사업화역량과 경쟁전략이 성장전망에 미치는 영향: 비즈니스모델 혁신의 매개효과를 중심으로)

  • Ahn, Mun Hyoung
    • Journal of Industrial Convergence
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    • v.20 no.8
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    • pp.1-13
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    • 2022
  • Although the number of venture start-ups has increased significantly, it is difficult to judge the success or failure based on short-term performance alone. The survival of a company cannot be guaranteed if it does not show sustainable growth prospects. As a growth factor for venture companies, the level of technology commercialization capability and competitive strategies are considered important. Recently, the emergence of innovative business models is creating new opportunities and driving the growth of numerous venture start-ups. This study tried to investigate the mediating effect of business model innovation in the relationship between technology commercialization capability, competitive strategy and the growth prospects of venture companies. For this, empirical analysis was conducted using the original data of the Research on the Precision Status of Venture Firms 2021. As a result, production, manufacturing, marketing capability, cost leadership and product differentiation had a positive(+) effect on growth prospects. The mediating effect of business model innovation between all factors except for manufacturing capacity and growth prospects was verified. This study expanded the scope of research by shedding new light on the factors influencing the long-term growth prospects of venture companies and revealing business model innovation as a new mediating variable. In future research, it is necessary to develop an objective measurement tool and to identify differences according to industrial characteristics.

Electrochemical Ion Separation Technology for Carbon Neutrality (탄소중립을 지향하는 전기화학적 이온 분리(EIONS) 기술)

  • Hwajoo Joo;Jaewuk Ahn;Sung-il Jeon;Jeyong Yoon
    • Applied Chemistry for Engineering
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    • v.34 no.4
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    • pp.331-346
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    • 2023
  • Recently, green processes that can be directly used in an energy-efficient and electrified society to achieve carbon neutrality are attracting attention. Existing heat and pressure-based desalination technologies that consume tremendous amounts of energy are no exception, and the growth of next-generation electrochemical-based desalination technologies is remarkable. One of the most representative electrochemical desalination technologies is electrochemical ion separation (EIONS) technology, which includes capacitive desalination (CDI) and battery desalination (BD) technology. In the research field of EIONS, various system applications have been developed to improve system performance, such as capacity and cyclability. However, it is very difficult to understand the meaning and novelty of these applications immediately because there are only a few papers that summarize the research background for domestic readers. Therefore, in this review paper, we aim to describe the technological advances and individual characteristics of each system in clear and specific detail about the latest EIONS research. The driving principle, research background, and strengths and weaknesses of each EIONS system are explained in order. In addition, this paper concluded by suggesting the future development and research direction of EIONS. Researchers who are just beginning out in EIONS research can also benefit from this study because it will help them understand the research trend.

GIS Information Generation for Electric Mobility Aids Based on Object Recognition Model (객체 인식 모델 기반 전동 이동 보조기용 GIS 정보 생성)

  • Je-Seung Woo;Sun-Gi Hong;Dong-Seok Park;Jun-Mo Park
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.200-208
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    • 2022
  • In this study, an automatic information collection system and geographic information construction algorithm for the transportation disadvantaged using electric mobility aids are implemented using an object recognition model. Recognizes objects that the disabled person encounters while moving, and acquires coordinate information. It provides an improved route selection map compared to the existing geographic information for the disabled. Data collection consists of a total of four layers including the HW layer. It collects image information and location information, transmits them to the server, recognizes, and extracts data necessary for geographic information generation through the process of classification. A driving experiment is conducted in an actual barrier-free zone, and during this process, it is confirmed how efficiently the algorithm for collecting actual data and generating geographic information is generated.The geographic information processing performance was confirmed to be 70.92 EA/s in the first round, 70.69 EA/s in the second round, and 70.98 EA/s in the third round, with an average of 70.86 EA/s in three experiments, and it took about 4 seconds to be reflected in the actual geographic information. From the experimental results, it was confirmed that the walking weak using electric mobility aids can drive safely using new geographic information provided faster than now.

Chemical Durability Test of Thin Membrane in Proton Exchange Membrane Fuel Cells (고분자전해질 연료전지에서 박막의 화학적 내구성 평가)

  • Sohyeong Oh;Donggeun Yoo;Sunggi Jung;Jihong Jeong;Kwonpil Park
    • Korean Chemical Engineering Research
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    • v.61 no.3
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    • pp.362-367
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    • 2023
  • Recently, research and development of proton exchange membrane fuel cells (PEMFC) membranes are progressing in the direction of thinning to reduce prices and improve performance. Demand for hydrogen-powered vehicles for commercial vehicles is also increasing, and their durability should be five times greater than those for passenger vehicles. Despite the thinning of the membranes, the durability of the membranes must be increased five times, so the improvement of the durability of the membranes has become more important. Since the acceleration durability evaluation time also needs to be shortened, the protocol using oxygen instead of air in the existing protocol was applied to a 10 ㎛ thin membrane to evaluate durability. The accelerated durability test (Open circuit voltage holding) was terminated at 720 hours. If the air-based department of energy (DOE) protocol was used, a lifespan of 450,000 km of driving hours would be expected, with a durability of about 1,500 hours. During the chemical durability evaluation, the active area of the electrode decreased by 51%, suggesting that catalyst degradation had an effect on membrane durability. Reducing the catalyst degradation rate is expected to increase membrane durability.

Deep Neural Network Analysis System by Visualizing Accumulated Weight Changes (누적 가중치 변화의 시각화를 통한 심층 신경망 분석시스템)

  • Taelin Yang;Jinho Park
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.3
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    • pp.85-92
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    • 2023
  • Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

Detecting Vehicles That Are Illegally Driving on Road Shoulders Using Faster R-CNN (Faster R-CNN을 이용한 갓길 차로 위반 차량 검출)

  • Go, MyungJin;Park, Minju;Yeo, Jiho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.105-122
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    • 2022
  • According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.

Design of Algorithm for Collision Avoidance with VRU Using V2X Information (V2X 정보를 활용한 VRU 충돌 회피 알고리즘 개발)

  • Jang, Seono;Lee, Sangyeop;Park, Kihong;Shin, Jaekon;Eom, Sungwook;Cho, Sungwoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.240-257
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    • 2022
  • Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.