• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.565-568
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• 2012

승차감이나 안전에 관련된 부분 중 하나인 자동차 시트는 차량 주행시 전달되는 충격이나 진동을 적절하게 흡수하여 승객에게 안락성을 제공한다. 또한 이러한 여건을 만족시키면서 승객의 안전을 보장하는 충분한 강성과 강도를 가져야 한다. 자동차 시트는 2가지의 모델로 설계를 하고 구조 해석을 하였다. 그 결과, 시트 백프레임의 모델 (b)가 (a)보다 적은 변형량과 피로 수명을 보였고. 모델의 중앙에 해당되는 허리부분에서 가장 많은 변형량과 파손 가능성을 보였다. 고유진동수를 적용한 진동해석에서, 모델(a)의 경우는 모델의 바깥쪽에서 안쪽으로 변형이 되었고, 모델(b)의 경우는 모델의 안쪽에서 바깥쪽으로 변형이 되었다. 전반적으로 모든 면에서 모델(b)가 (a)보다 구조적으로 안전하다고 사료된다.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.127-132
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• 2012

In the Seoul metropolitan bus network, it may be necessary for a bus passenger to pick up a parcel, which has been purchased through e-commerce, at his or her convenient bus stop on the way to home or office. The flow-capturing location-allocation model can be applied to select pickup points for such bus stops so that they maximize the captured passenger flows, where each passenger flow represents an origin-destination (O-D) pair of a passenger trip. In this paper, we propose a fast heuristic algorithm to select pickup points using a large O-D matrix, which has been extracted from five million transportation card transactions. The experimental results demonstrate the bus stops chosen as pickup points in terms of passenger flow and capture ratio, and illustrate the spatial distribution of the top 20 pickup points on a map.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.472-479
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• 2024

Half of the world's total population lives in cities, continuous urbanization is progressing, and the urban population is expected to exceed two-thirds of the total population by 2050. To resolve this phenomenon, the Korean government is focusing on building a new urban air mobility (UAM) industrial ecosystem. Airlines are also part of the UAM industry ecosystem and are preparing to improve efficiency in safe operations, passenger safety, aircraft operation efficiency, and punctuality. This study performs demand forecasting using time series data on the number of daily passengers on Korean Air's Gimpo to Jeju route from 2019 to 2023. For this purpose, statistical and machine learning models such as SARIMA, Prophet, CatBoost, and Random Forest are applied. Methods for effectively capturing passenger demand patterns were evaluated through various models, and the machine learning-based Random Forest model showed the best prediction results. The research results will present an optimal model for accurate demand forecasting in the aviation industry and provide basic information needed for operational planning and resource allocation.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.2
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• pp.116-128
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• 2011

Some subway passengers may want to have their fresh vegetables purchased through internet at a service facility within the subway station of the Metropolitan Seoul subway system on the way to home, which raises further questions about which stations are chosen to locate service facilities and how many passengers can use the facilities. This problem is well known as the pickup problem, and it can be solved on a traffic network with traffic flows which should be identified from origin stations to destination stations. Since flows of the subway passengers can be found from the smart card transaction database of the Metropolitan Seoul smart card system, the pickup problem in the Metropolitan Seoul subway system is to select subway stations for the service facilities such that captured passenger flows are maximized. In this paper, we have formulated a model of the pickup problem on the Metropolitan Seoul subway system with subway passenger flows, and have proposed a fast heuristic algorithm to select pickup stations which can capture the most passenger flows in each step from an origin-destination matrix which represents the passenger flows. We have applied the heuristic algorithm to select the pickup stations from a large volume of traffic network, the Metropolitan Seoul subway system, with about 400 subway stations and five millions passenger transactions daily. We have obtained not only the experimental results in fast response time, but also displayed the top 10 pickup stations in a subway guide map. In addition, we have shown that the resulting solution is nearly optimal by a few more supplementary experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.2
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• pp.220-227
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• 1998

In substitution of beam-nonlinear spring model for real-car, it may have errors due to complicated characteristics of joint and overestimation of joints stiffness. In this research, a method for the joint modeling was suggested by nonlinear static and dynamic analyses of beam and shell joint models and verified by the application of accomplished joint modeling method to simplified full car model. In consequence, modified simplified full car model was improved in local acceleration and rigid wall force. Finally, the frontal crash analyses with the dummy were established and the accelerations of accelerations of head, chest and pelvis had good agreements with those of shell model.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.1
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• pp.99-106
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• 2023

글로벌 팬데믹 사태는 항공 수요에 부정적인 영향을 끼치는 요소 중 하나다. 글로벌 팬데믹으로 인해 한국은 2020년과 2021년의 항공 승객 수가 2019년 대비 각각 68.1%와 47% 감소했다. 본 연구는 지난 20여년 동안 발생한 4대 팬데믹 특성을 분석, 전염병의 영향을 연구하는 것을 목표로 한다. SARS, H1N1, MERS 및 COVID-19의 발생기간 동안 한국의 항공 여객 및 화물 수요에 대한 실증 데이터를 활용하여 영향력을 분석한다. 또한 머신러닝 회귀 모델을 구축하여 향후 발생할 다른 전염병 대한 항공 수요를 예측하고자 한다. 연구 결과, 전염병이 항공 운항편수와 승객에 부정적인 영향을 미친다는 사실을 발견하였다. 반면화물 수송에는 긍정적인 영향을 미친다는 분석 결과를 도출하였다. 본 분석에 활용되는 회귀 모델은 팬데믹 기간 동안 항공수요를 예측하는 데 평균 86.8%의 기능을 보였다. 또한 본 연구는 특정 국가의 팬데믹 상황보다 전 세계적인 팬데믹 상황이 항공 운송 수요에 더 많은 영향을 미친다는 것을 보여준다.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.277-282
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• 2004

In order to investigate the small female occupant behavior and accompanying injury mechanisms in vehicular trash event, a finite element model of $5^{th}$ percentile female has been developed. The model consists of articulated rigid body, which represents the morphology of small female body, and internal components with anatomical details. Articulated rigid body model serves as a basic platform for joining the detail internal skeletons and organs, while itself can be used for representing the overall kinematics of small female occupant. The modeling details such as anthropometry and finite element structure as well as validation results for the articulated rigid body model are introduced in this paper. The second part of the modeling, i.e. the internal components with anatomical details of small female are presented in subsequent part II of the paper.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.263-264
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• 2003

서울의 지하철은 1974년 1호선이 개통된 이래로 현재 8개 노선 262개 역사가 개통/운행되고 있으며 약 40％의 수송 분담율을 담당하고 있다. 이는 건설중이거나 검토 중에 있는 지하역사를 고려할 때 계속해서 증가할 것으로 예상된다. 이와 같은 높은 수송분담율은 지하철 이용승객이 늘고 있으며 동시에 이용승객이 지하철을 이용하는 동안 지하철 시스템내의 실내공기환경에 노출되는 시간이 길어지고 있음을 의미한다. 최근에 수행된 연구결과에 의하면 지하철 시스템내의 공기질, 특히 지하역사내의 공기질은 역사내부의 여러 가지 영향인자들에 의해 밀집되는 것으로 판단된다. (중략)

• Smart Media Journal
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• v.12 no.11
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• pp.57-66
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• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.283-284
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• 2011

본 연구는 승객이 국내 공항에서 셀프 체크인 kiosk를 사용하려는 행동 의도에 관해, 개인적 특성과 상황적 변수의 조절효과를 실증 분석하는 데 목적을 두고 있다. 공항 Kiosk를 사용함으로써 승객과 항공사, 공항은 비용 절감의 이점을 누릴 수 있다. 그에 따라 항공사와 공항 측에서는 이러한 경제적 효용을 보다 많은 사람들이 누릴 수 있도록 하기 위해 kiosk의 보급을 늘이고자 하는 입장이다. 그럼에도 불구하고 공항kiosk의 사용률은 아직까지 낮은 수준에 그치고 있으며 그에 관한 연구도 활발히 이루어지지 않고 있다. 이에 본 연구에서는 확장된 기술수용모델을 기반으로 하여 개인적 특성과 상황적 변수가 승객의 kiosk 사용의도에 미치는 차별적 영향에 관해 분석하고자 한다.