• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.65-70
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• 2010

AC traction power supply system has adopted autotransformer (AT) feeding method. This system has an advantage as long feeding distance. However, the countermeasure for voltage drop should be considered, because load capacity grows larger and headway grows shorter in recent electric railway system. This paper proposes the improved system configuration to enhance voltage drop in ac railway system without additional power electronic device. That is to increase turn ratio between contact wire and rail of AT. By modifying turn ratio of AT at SSP or SP, collecting voltage on train will be enhanced.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.43-54
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• 2000

이 연구는 버스정보 시스템 설계에 필요한 운행시격 결정과 통행시간 예측을 위한 알고리즘 개발을 다룬다. 운행시격 결정 문제는 버스와 같은 대중교통 수단을 운영하는데 중요한 요소 중에 하나이다. 기존 연구는 버스 운행비용과 승객비용의 합을 최소로 하는 운행시 격을 찾는데 초점을 두고 이다. 이때 승객비용이란 승객 대기비용과 승객 교통비용의 합으로 이루어진다. 그런데 우리나라와 같이 버스회사 수입이 전액 운행수입에만 의존하는 경우엔 이러한 접근 방식이 타당하지 않다. 기존의 방식과 다르게 승객비용으로 승객 이탈비용을 사용하여 버스의 최적 운행시 격을 구하는 것이 이 연구의 목적이다. 먼저 정류장이 하나인 경우에 대해 해석적 방법으로 풀고, 정류장이 여러 개인 경우에 대해서는 시뮬레이션 기법을 적용한다. 또한 이 연구는 신뢰성이 높고 정확한 통행시간 예측정보를 산출하기 위해 2 단계 예측 기법과 전문가시스템을 이용하는 자료융합 알고리즘을 개발한다. 정확한 정보를 제공하려면 교통정보 수집원을 통해 얻는 자료가 정확해야 하고, 또한 교통상황 변화에 따라 실시간으로 통행시간을 예측하는 것이 필요하다. 이 연구는 AVL(Automatic Vehicle Location)시스템을 이용한 버스정보시스템에서 실시간 데이터와 과거 데이터를 융합하여 통행시간을 예측하는 알고리즘을 개발한다. AVL 데이터를 수집하는 과정에서는 경제성을 고려하여 데이터를 수집한다. 그리고, 버스의 운행관리와 정확한 도착예정시간을 예측하기 위해 AVL시스템을 통해 얻은 데이터의 패턴을 분석하고 유고상황을 감지한다.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.73-82
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• 2004

신호 교차로에서 포화차두시간에 영향을 미치는 영향인자는 도로조건, 교통조건, 환경조건으로 분류된다. 이러한 요인들의 복합적인 관계가 포화차두시간에 영향을 미친다. 현재 포화교통류율은 이상적인 조건일 때의 포화차두시간을 산출하고, 이를 이용해서 기본 포화교통류율을 구하고, 여기에 좌 우회전, 차로폭, 경사, 중차량 보정계수을 고려함으로써 특정 차로군의 포화교통류율을 산정하고 있다. 포화차두시간에 영향을 미치는 인자들 중에서 정량적으로 나타내기 어려운 인자 즉, 퍼지적 성격을 가진 인자들은 고려하지 않고 있다. 따라서 본 연구에서는 퍼지 근사추론 방법을 이용하여 정성적 인자의 영향을 고려한 모형을 구축하였다. 모형의 입력자료는 강우조건과 주변밝기의 정도, 중차량 구성비의 언어적 표현를 사용하였다. 이러한 변수들에 대하여 설문조사를 통해서 퍼지집합의 멤버쉽함수를 설정하였으며. 이에 기초하여 교차로에서 각 조건별로 포화차두시간을 관측하였다. 이러한 현장 관측치를 바탕으로 퍼지 제어규칙을 설정하고 모형을 구축하였다. 모형의 평가는 추론치와 실측치를 비교함으로써 이루어 졌으며, 결정계수인 $R^2$와 평균절대오차(MAE)와 평균제곱오차(MSE)를 사용하여 분석한 결과 본 모형의 설명력이 높은 것으로 평가되었다. 본 연구의 과정에서 강우에 의한 교통용량 감소는 중차량 구성비가 클수록 주변밝기의 정도가 나쁠수록 더욱 큰 것으로 나타났으며 그 감소율은 5.3%에서 21.8%에 이르는 넓은 범위의 값을 보였고. 주변밝기 정도에 따른 교통용량 감소는 4.7$\sim$7.5% 수준으로 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.77-86
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• 1993

Recently it is reported in many countries that highway bridges are seriously damaged due to increasing volume of overloaded heavy vehicles. The safety of bridges are highly related to the design load level and the characteristics of extreme load effect induced by traffic loads during its lifetime. The maximum structural load effect during lifetime may be produced by simultaneous loading of trucks with moderate weights on a bridge rather than by single loading of extremely heavy trucks. In this study, a simulation technique to estimate extreme load effect due to traffic loadings has been developed, in which important characteristics of traffic loadings, such as heavy vehicle proportion, traffic mode, vehicle weights, headway distribution. daily traffic volume, etc., should be properly considered. In addition. sensitivity analysis on those factors have been performed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.438-442
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• 2003

For an efficient sliding mode control system stability and chattering avoidance should be guaranteed. A continuation method using boundary layer is well known as one solution for this. However since not only model uncertainties and disturbances but also control task itself is variable. it is practically impossible to set controller parameters - control discontinuity, control bandwidth, boundary layer thickness - in advance. In this paper first an adaptation law of control discontinuity is introduced to assure system stability and then fuzzy logic based tuning algorithm of design parameters is applied based on monitored performance indices of tracking error, control chattering, and model precision. In the end maximum control bandwidth not exciting unmodeled dynamics and minimum control discontinuity, boundary layer thickness making system stable and free of chattering are found respectively. This eliminates control chattering and enhances control accuracy as much as possible under given control situation. In order to demonstrate the validity of the proposed algorithm safe headway maintenance control for autonomous transportation system is simulated. The control results show that the proposed algorithm guarantees system stability all the time and tunes control parameters consistently and in consequence implements an efficient control in terms of both accuracy and actuator chattering.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.68-75
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• 1998

The Intelligent Cruise Control system, ICC, is a driver assisting system for controlling relative speed and distance between two vehicles in the same lane. The ICC may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting the speed also to that of a slower one ahead. This paper presents a real-time self-tuning fuzzy control algorithm to develop ICC. The self-tuning fuzzy control law is adopted to reduce the effects of nonlinearities of the vehicle and various road environments. In the self-tuning algorithm an interior penalty method is applied to preserve the inherent order of membership functions and is modified as an on-line algorithm for real time application. Via simulations, the performance of the suggested control algorithm is compared with a PID and a fuzzy control without self-tuning. The suggested control algorithm is implemented on PRV III and the results of the test driving on a local road are given.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.165-189
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• 2013

The advance of the smart working environment came the expectation that it would innovate and revolutionize the way people work, particularly in a society where smart work is readily available for creating a collaborative and 'connected' business. One of the core infrastructure elements for making smart work a viable option is the smart work center, the promotion of which requires a new form of 'smart work center business model' that can satisfy the purposes of both public services and private businesses. This calls for collaboration between the public and private sectors. Recently a number of businesses have been making significant headway in the creation of a new environment for business support and collaboration by adopting a sharing economy business model in their offices. The so-called 'Coworking Space' is an advanced form of business environment in the emerging 'smart work' era, and comes with the benefits of reduced costs as a result of sharing office space and knowledge sharing through the use of human networks. This paper describes the framework of a 'smart work center business model based on the sharing economy' using a BMC (Business Model Canvas), with an understanding of the characteristics inherent to the smart work center and the sharing economy. It was on the basis of this framework that a smart work center model for business incubation and startup, a private smart work center model for childcare services, and a community marketplace model with a global network were developed.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.496-500
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• 1998

Not merely running at the designated constant speed as the classical cruise control, the adaptive cruise control (ACC) maintains safe headway distance when the front is blocked by other vehicles. One of the most essential part of ACC System is the range sensor which can measure the position and speed of all objects in front continuously, ignore all irrelevant objects, distinguish vehicles in different lanes and lock on to the closest vehicle in the same lane. In this paper, the hierarchical object recognition algorithm (HORA) is proposed to process raw scanning laser data and acquire valid distance to target vehicle. HORA contains two principal concepts. First, the concept of life quantifies the reliability of range data to filter off the spurious detection and preserve the missing target position. Second, the concept of conformation checks the mobility of each obstacle and tracks the position shift. To estimate and predict the vehicle position Kalman filter is used. Repeatedly updated covariance matrix determines the bound of valid data. The algorithm is emulated on computer and tested on-line with our ACC vehicle.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.261-267
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• 2006

The required storage inventory is a very important decision variable which determines the storage capacity of a container terminal. Generally, the required storage inventory is dependent upon such factors as ship headway, allowable dwell time of containers, loading/unloading time per ship, and so on. Until now, the required storage inventory is estimated under the assumption that the factors are deterministic in several studies. However, this study proposes how to estimate a required storage inventory satisfying the required service level under the assumption that a containership's load size is probabilistic. Numerical experiments, which use a simulation show that the proposed method can estimate more adequately the maximum storage inventory than other methods under a probabilistic environment.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.111-119
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• 2011

The noise prediction model, KRON-2006, in South Korea has been developed for obtaining the average noise level. The model is based on an outdoor sound propagation method based on ISO9613 and ASJ Model-1998 and supports the analysis of the linear noise source, such as highway, for obtaining Leq. Because of that, the model can't obtain Lmax, Lmin from the time series noise profile based on traffic at every moment. In order to address this problem, the real time noise prediction model based on traffic simulation using GIS model and algorithm is proposed. It can predict the vehicle point noise level based on vehicle type, speed generated from traffic simulation by using headway and obtain Lmax, Lmin as integrating the noise profile generated from it at every moment. An evalution of the noise prediciton model using field measurements finds good agreement between predicted and measured noise levels at 1m, 8m, 15m from curb of the near side lane.