• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2000.11a
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• pp.453-459
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• 2000

개개인의 생활 수준 향상으로 자동차가 개인 교통 수단이나 레저 생활용으로 더욱 많이 활용되면서 장시간 운전이 늘어감에 따라, 운전자의 신체적 피로는 운전 중의 사고의 원인이 되고 있으며, 장시간 운전시의 피로감의 원인이라고 할 수 있는 엔진과 노면으로부터 인체에 전달되는 진동에 대한 대비책으로, 시트 부분의 내진 및 감쇠 설계가 실제로 운전자가 느끼는 승차감 즉 안락성에 결정적인 역할을 한다고 볼 수 있다. 국내의 경우 자동차 시트 기술은 대부분 외국 기술에 의존하고 있는 실정이어서 전문적인 연구는 매우 미흡한 실정이다.(중략)

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.39-40
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• 2022

최근 전동 킥보드, 전동휠, 전기 자전거 등 개인형 이동수단(Personal Mobility)의 보급이 늘면서 관련 인명 교통사고가 급증하고 있다. 본 논문에서는 개인형 이동수단의 사용위험 및 사고 감소를 목적으로, 딥러닝 객체탐지 기술을 적용하여 다양한 위험요소를 증강현실 기술을 기반으로 한 HMD(Helmet mounted display)에 표시하는 '딥러닝 객체 인식과 증강현실을 적용한 개인 이동장치를 위한 HMD(Helmet Mounted Display) 어플리케이션'을 설계한다. 제시하는 방법은 실시간으로 수집된 전방의 실시간 영상 정보를 객체 탐지 알고리즘을 통해 위험요소 및 안전한 주행을 보조하는 객체를 감지하고 증강현실을 적용해 사용자에게 적절한 운전 보조장치 및 기능을 제공한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.38-41
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• 2004

납치ㆍ유괴는 개인의 자유로운 활동에 많은 영향을 미치는 위험요소이다. 이러한 위험 요소로부터 벗어나기 위해서 개인의 위치를 확인할 수 있는 시스템이 절실히 필요하다. 위성 항법 시스템(Global Positioning System, GPS)은 기상 상태에 상관없이 지구 전역에서 사용 가능한 효율적인 항법 시스템으로 위치정보에 대한 지표를 제공한다. GPS는 현재 지속적인 개발에 의해 수신 모듈의 소형화 고성능화가 이루어지고 있으며, 고정 또는 이동하는 시스템의 위치정보를 제공한다. GPS 시스템을 개인이 휴대하게 되면 개인의 이동경로를 확인할 수 있게 된다. 일반적으로 개인의 이동경로는 생활권역 내에 특정 지역으로 한정되는 경우가 많으며 이동경로 자체도 주된 교통수단과 맞물려 일정한 패턴을 형성한다. 이러한 이동특성에 착안하여 본 논문에서는 개인 안전을 위해 GPS의 위치정보와 소프트 컴퓨팅 기법을 접목한 시스템을 휴대한 사용자의 이동경로를 학습하여 개인의 안전을 보장하는 방법을 제안한다.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.301-310
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• 1998

사람들은 나이가 들어감에 EK라 건강상태와 신체적 기능이 쇠퇴한다. 그래서 대부분의 고령자들은 이동이 제한되고, 교통시스템의 이용에 어려움을 겪게 된다. 본 연구는 60세 이상의 고령자를 대상으로 횡단보도, 육교와 같은 횡단시설의 이용에 대한 고령자들의 교통특성을 분석하는 것을 목적으로 하고 있다. 이를 위해서 본 연구에서는 실태조사와 설문조사를 행하여 고령자들의 횡단보도, 육교 등의 횡단시설의 이용현황을 파악하였다. 또한, 고령자들의 연령, 성별 건강상태, 보행능력, 계단승하강능력 등의 개인속성들 사이의 관련성을 분석하였다. 분석결과, 고령자들의 횡단시설이용이 그들의 건강상태와 신체적 기능의 장애로 인해 매우 제한된다는 것을 보여주고 있어, 고령자의 신체기능 및 교통수단 이용특성을 고려한 교통시설의 정비 및 확충이 필요함을 알 수 있었다.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.304-313
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• 2012

Uncertainty increases as a result of environment change and change of individual decision-making in extreme weather. This study consider individual decision-making which has been not covered until now. The purpose of this study is making Agent-Based Model to predict it more accurate that how much change travel demand in heavy rain and heavy snow. Through this model, it can be utilized to forecast travel demand, changes in travel behavior and traffic patterns. It will be also possible to predict discomfort index and risk of accidents.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.511-524
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• 2017

This study aims to evaluate the availability of ABM (Active-Based Model), FEATHERS, as a policy evaluation tool. To achieve the goal, scenario analysis on flexible working policy was conducted to measure its impact on activity-travel behavior. As a consequence, there seems no significant change in worker's daily life, other than mitigating traffic congestion due to decreasing commuting travel in the rush hour. The result of VKT (vehicle kilometers traveled) shows an opposite pattern according to given household/individual constraints. The scenario analysis on telecommuting indicates a decreasing trend in both travel frequency and distance because of the diminished number of commuting trips. As the activity space of telecommuters is shifted to a residential area, there are more short-distance trips by using non-motorized transport, which leads to decrease in VKT (using a private vehicle). Thus, the sensitivity of VKT by population groups varies due to transport mode shift (between personal and another mode) and growing non-work trips (using a private mode). This study found few things. First, it is necessary to evaluate the details of policy impact by population groups since it can be varied depending on household/individual characteristics. Second, the case study shows a promising performance of ABM as policy measurement that provides reality in policy evaluation. Third, ABM allows us to do more accurate analysis (i.e. time-series analysis by population groups) of policy assessment than those of FSM (Four-Step Model). Lastly, a further effort in data collection, literature review, and expert survey should be made to enhance the accuracy and confidence of future research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.114-131
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• 2023

Personal Mobility (PM)-related accidents have increased rapidly since PM use was activated. In response to the increase in these accidents, the government strengthened regulations for PM users on May 13, 2021. The number of the accidents in which the PM user was a victim decreased significantly. In contrast, the increasing number of accidents in which PM user was the offender did not decrease significantly. In most of these accidents, the PM user was the offender who crashed into pedestrians. Hence, the safety of pedestrians is threatened. Therefore, this study analyzed the factors, such as the regulations, urban built environment, and personal characteristics, affecting the severity of PM-pedestrian accidents by focusing on PM-pedestrian crashes. This study analyzed the PM-pedestrian accidents in Seoul from 2020 to 2021 using binary logistic regression model. Through these results, this study proposed the policy implications.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.157-168
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• 2009

The random utility theory and the multinomial logit model (including a more recent variant--the mixed multinomial logit) derived from it have constituted a back bone for theoretical and empirical analyses of various travel demand features including mode choice. In their empirical applications, however, it is customary to specify random utilities which are linear in modal attributes such as time and cost, and in socio-economic variables. The linearity helps easy derivation of important information such as value of travel time savings by calculating marginal rate of substitution between time and cost. In this paper the author focuses on the very linearity of the random utilities. Taking into account the fact that the mode chooser is also labour supplier, commodity consumer as well as leisure-seeker, the author sets up a maximization model of the traveller, which encompasses various economic activities of the traveller. The author derive from the model the indifference curve defined on the space of modal attributes, time and cost and investigate under what conditions the random utility of the traveller becomes linear. It turns out that there exist the conditions under which the random utility is really linear in modal attributes, but the property does not hold when the traveller has a corner solution on the space of modal attributes, or when the primary utility function of the traveller is directly affected by labour provided and/or the travel time itself. As a corollary of the analysis, a random utility is suggested, approximated up to the second order of the variables involved for empirical studies of the field.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.544-553
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• 2014

Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.