• 제목/요약/키워드: 차량

검색결과 13,312건 처리시간 0.043초

Improved Estimation of Hourly Surface Ozone Concentrations using Stacking Ensemble-based Spatial Interpolation (스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상)

  • KIM, Ye-Jin;KANG, Eun-Jin;CHO, Dong-Jin;LEE, Si-Woo;IM, Jung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • 제25권3호
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    • pp.74-99
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    • 2022
  • Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

Analysis of domestic and foreign future automobile research trends based on topic modeling (토픽모델링 기반의 국내외 미래 자동차 연구동향 비교 분석: CASE 키워드 중심으로)

  • Jeong, Ho Jeong;Kim, Keun-Wook;Kim, Na-Gyeong;Chang, Won-Jun;Jeong, Won-Oong;Park, Dae-Yeong
    • Journal of Digital Convergence
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    • 제20권5호
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    • pp.463-476
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    • 2022
  • After industrialization in the past, the automobile industry has continued to grow centered on internal combustion engines, but is facing a major change with the recent 4th industrial revolution. Most companies are preparing for the transition to electric vehicles and autonomous driving. Therefore, in this study, topic modeling was performed based on LDA algorithm by collecting 4,002 domestic papers and 68,372 overseas papers that contain keywords related to CASE (Connectivity, Autonomous, Sharing, Electrification), which represent future automobile trends. As a result of the analysis, it was found that domestic research mainly focuses on macroscopic aspects such as traffic infrastructure, urban traffic efficiency, and traffic policy. Through this, the government's technical support for MaaS (Mobility-as-a-Service) is required in the domestic shared car sector, and the need for data opening by means of transportation was presented. It is judged that these analysis results can be used as basic data for the future automobile industry.

A Study on Artificial Intelligence Ethics Perceptions of University Students by Text Mining (텍스트 마이닝으로 살펴본 대학생들의 인공지능 윤리 인식 연구)

  • Yoo, Sujin;Jang, YunJae
    • Journal of The Korean Association of Information Education
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    • 제25권6호
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    • pp.947-960
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    • 2021
  • In this study, we examine the AI ethics perception of university students to explore the direction of AI ethics education. For this, 83 students wrote their thoughts about 5 discussion topics on online bulletin board. We analyzed it using language networks, one of the text mining techniques. As a result, 62.5% of students spoke the future of the AI society positively. Second, if there is a self-driving car accident, 39.2% of students thought it is the vehicle owner's responsibility at the current level of autonomous driving. Third, invasion of privacy, abuse of technology, and unbalanced information acquisition were cited as dysfunctions of the development of AI. It was mentioned that ethical education for both AI users and developers is required as a way to minimize malfunctions, and institutional preparations should be carried out in parallel. Fourth, only 19.2% of students showed a positive opinion about a society where face recognition technology is universal. Finally, there was a common opinion that when collecting data including personal information, only the part with the consent should be used. Regarding the use of AI without moral standards, they emphasized the ethical literacy of both users and developers. This study is meaningful in that it provides information necessary to design the contents of artificial intelligence ethics education in liberal arts education.

Simultaneous Estimation of State of Charge and Capacity using Extended Kalman Filter in Battery Systems (확장칼만필터를 활용한 배터리 시스템에서의 State of Charge와 용량 동시 추정)

  • Mun, Yejin;Kim, Namhoon;Ryu, Jihoon;Lee, Kyungmin;Lee, Jonghyeok;Cho, Wonhee;Kim, Yeonsoo
    • Korean Chemical Engineering Research
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    • 제60권3호
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    • pp.363-370
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    • 2022
  • In this paper, an estimation algorithm for state of charge (SOC) was applied using an equivalent circuit model (ECM) and an Extended Kalman Filter (EKF) to improve the estimation accuracy of the battery system states. In particular, an observer was designed to estimate SOC along with the aged capacity. In the case of the fresh battery, when SOC was estimated by Kalman Filter (KF), the mean absolute percentage error (MAPE) was 0.27% which was smaller than MAPE of 1.43% when the SOC was calculated by the model without the observer. In the driving mode of the vehicle, the general KF or EKF algorithm cannot be used to estimate both SOC and capacity. Considering that the battery aging does not occur in a short period of time, a strategy of periodically estimating the battery capacity during charging was proposed. In the charging mode, since the current is fixed at some intervals, a strategy for estimating the capacity along with the SOC in this situation was suggested. When the current was fixed, MAPE of SOC estimation was 0.54%, and the MAPE of capacity estimation was 2.24%. Since the current is fixed when charging, it is feasible to estimate the battery capacity and SOC simultaneously using the general EKF. This method can be used to periodically perform battery capacity correction when charging the battery. When driving, the SOC can be estimated using EKF with the corrected capacity.

A Study on Validation of Omnidirectional VR Treadmill by Comparison of Spatial Orientation Skills (공간지향 능력 비교를 통한 전방향 VR 트레드밀의 유효성 검증 연구)

  • Park, Hyunchul;Oh, Taeho;Kim, Inhi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제21권5호
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    • pp.15-27
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    • 2022
  • An omnidirectional VR treadmill is a highly-immersive walking simulator that allows identical body movements, such as walking, running, and sitting. However, the operation difficulty of an omnidirectional VR treadmill may cause data reliability problems. Therefore, this study aims to verify the effectiveness of a VR treadmill by comparing the ability to orient in the real and virtual worlds spatially. For this purpose, a rotating and searching path experiment was conducted with participants. This experiment showed that there was no statistically significant difference in the ability of the participants to orient in the real and virtual worlds spatially. In addition, the omnidirectional VR treadmill requires an adaptation time for the users due to the difficulty in the treadmill operation. However, there was no significant difference in the difficulty felt by the participants according to the adaptation time. Hence, these findings supported the possibility of collecting realistic walking data without safety concerns through an omnidirectional VR treadmill. Furthermore, this treadmill could be used in future research to solve problems directly related to pedestrian safety, such as the interaction between vehicles and pedestrians.

An Investigation for Driving Behavior on the On-Ramp Merging Section in Urban Underground Roads Using a Driving Simulator (주행 시뮬레이터를 활용한 도심 지하도로 유입연결로 합류부 주행행태 분석)

  • Seungwon Jeong;Soohwan Kim;Dongmin Lee;Gunki Jung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제21권6호
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    • pp.97-114
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    • 2022
  • Unlike ground roads, the on-ramp merging section of underground roads cannot be seen by drivers of main road due to tunnels. In this study, a driving simulator was used for analysis, and virtual driving experiments were carried out to assess the driver's visibility for different design factors. The driver's driving behavior was analyzed by setting scenarios considering the length of chevron markings and the approach speed from the main road. The results of the analysis were used to determine the design factors for ensuring visibility when constructing the virtual driving environment for each scenario. These factors, including speed, lane change points, and driver's gaze ratios, were reviewed for significance using a statistical approach. As a result, in scenarios with a higher approach speed from the main road, it was discovered that there was a difference in driver's behavior between specific scenarios depending on the length of the section with chevron markings. Based on these findings, this study suggests implications and feasible solutions to improve driver safety on the on-ramp merging section of underground roads.

Classification and Prediction of Highway Accident Characteristics Using Vehicle Black Box Data (블랙박스 영상 기반 고속도로 사고유형 분류 및 사고 심각도 예측 평가)

  • Junhan Cho;Sungjun Lee;Seongmin Park;Juneyoung Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제21권6호
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    • pp.132-145
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    • 2022
  • This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

Development of IoT-Based Disaster Information Providing Smart Platform for Traffic Safety of Sea-Crossing Bridges (해상교량 통행안전을 위한 IoT 기반 재난 정보 제공 스마트 플랫폼 개발)

  • Sangki Park;Jaehwan Kim;Dong-Woo Seo
    • Journal of Korean Society of Disaster and Security
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    • 제16권1호
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    • pp.105-113
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    • 2023
  • Jeollanam-do has 25 land-to-island and island-to-island bridges, the largest number in Korea. It is a local government rich in specialized marine and tourism resources centered on the archipelago and the sea bridges connecting them. However, in the case of sea-crossing bridges, when strong winds or typhoons occur, there is an issue that increases anxiety among users and local residents due to excessive vibration of the bridge, apart from structural safety of the bridge. In fact, in the case of Cheonsa Bridge in Shinan-gun, which was recently opened in 2019, vehicle traffic restrictions due to strong winds and excessive vibrations frequently occurred, resulting in complaints from local residents and drivers due to increased anxiety. Therefore, based on the data measured using IoT measurement technology, it is possible to relieve local residents' anxiety about the safety management of marine bridges by providing quantitative and accurate bridge vibration levels related to traffic and wind conditions of bridges in real time to local residents. This study uses the existing measurement system and IoT sensor to constantly observe the wind speed and vibration of the marine bridge, and transmits it to local residents and managers to relieve anxiety about the safety and traffic of the sea-crossing bridge, and strong winds and to develop technologies capable of preemptively responding to large-scale disasters.

A Study on Non-Destructive Safety Evaluation Platform of Internal Defects of the Composite Hydrogen Tank using Finite Element Analysis (유한요소해석을 이용한 수소압력용기 비파괴 시험 평가 플랫폼의 안전성 기준 개발 연구)

  • Yongwoo Lee
    • Journal of Platform Technology
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    • 제10권4호
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    • pp.3-10
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    • 2022
  • In this study, damage resulting from internal flaws was investigated by finite element analysis for the safety evaluation of a non-destructive testing platform for hydrogen pressure vessels. A specimen was modeled and calculated using finite element analysis to determine material properties in accordance with the parameters of the composite material in order to assess the safety of the Type 4 hydrogen pressure vessel. Through this, flaws in the hydrogen pressure vessel were modeled, and test conditions were provided in accordance with rules to look into whether there was safety. Delamination, foreign object, and vertical cracks were modeled for internal flaws, and damage was examined in accordance with failure criteria. As the delamination defect approached the interior of the hydrogen pressure tank, it became more likely to cause damage. Additionally, as the crack depth grew in the case of vertical cracks, the likelihood of crack propagation rose. On the other hand, it was anticipated that the foreign item defect would suffer more damage from the outside in. A non-destructive testing platform will be used to assess the safety of fuel cell vehicles that are already in operation in future research.

A Study on the Calculation of Dynamic Yellow Signal Time Based on Approach Speed and Collision Points (접근속도와 상충지점 기반 동적황색신호시간 산정 연구)

  • Hyunho Son;Sanghoon Sung;Choulki Lee;Hyeon Soo Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제22권4호
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    • pp.14-34
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    • 2023
  • The purpose of this study was to calculate the appropriate yellow-signal time for intersections, to find out the relationship between the approach speed and intersection width when calculating the time, and to secure safety by minimizing conflicts and dilemma sections in intersections that change according to the signal operation. For this purpose, 6,824 data points from 5 intersections were collected and analyzed. The main results of the study are as follows. First, the approach speed of individual vehicles in different lanes was analyzed, and the width of an intersection was defined by considering the conflict in each direction. Second, we developed a multiple regression model based on the approach speed and conflict points, which compensated for the problems of an existing formula. Third, a standard table is presented for applying the appropriate yellow-signal time according to the approach speed and intersection width based on a development formula. A method is also presented to determine the safety of the length of the dilemma according to the change in the yellow-light time by presenting a calculation table that can cross-analyze the yellow-signal time and a dilemma section using the relationship.