• Proceedings of the KOR-KST Conference
• /
• 1998.10a
• /
• pp.73-82
• /
• 1998

본 연구의 목적은 일주일간 조사된 개인통행행태를 고려한 각 특성별 통행발생예측 방법을 제시하는데 있다. 이를 위하여 일주일간 통행빈도수의 차이를 고려한 집단간 차이를 검정하고, 그 원인을 분석하여 이에 따른 특성별 개인 통행발생예측 모형을 정립하였다. 전체 표본의 각 특성별 개인 내부 변이성을 분석해 본 결과 기간의 차이에 따른 개인 통행행태의 변화는 직업별, 나이별, 성별, 차량소유 유무, 주택소유 형태, 통행목적, 통행수단, 가구원수에 따라 집단간 차이를 보여주었다. 이러한 변수를 이용한 통행발생 예측모형의 분석결과 개인소득이 높을수록, 주책을 자가로 소유한 경우, 자동차를 소유한 경우, 학생일수록, 유직일수록 개인 통행발생량이 많은 것으로 분석되었다. 반면, 아니는 연령대가 높아질수록 통행수가 적어졌다.

• Proceedings of the KOR-KST Conference
• /
• 2002.02a
• /
• pp.45-77
• /
• 2002

교통혼잡 문제가 점점 심각해짐에 따라 대중교통의 중요성은 날로 부각되며, 대중교통을 지원하기 위한 정책들이 속속 입안되고 있어 대중교통을 심도 있게 분석할 수 있는 틀의 개발은 필연적이라 할 수 있다. 이에 본 연구는 대중교통 통행배정모형 개발과 대중교통 기종점통행량(OD) 추정을 목적으로 수행되었다. 대중교통 통행배정모형의 개발부분에서는 기존의 대중교통 통행배정모형이 개별차량과 다른 대중교통의 특성을 정확히 반영하고 있지 못하다는 한계를 극복하고자, 최적경로 탐색에는 유전자 알고리즘(Genetic Algorithm)을 통행량 배정에는 로짓모형을 기반으로 한 확률적 통행량 배정모형(Stochastic Network Loading Model)을 이용하여 TATSN 모형을 개발하였다. 그리고, 대중교통 기종점통행량의 추정은 전통적인 기종점통행량 추정 방법인 기종점조사 방법이 시간과 비용이 과대하게 소요된다는 단점을 인식하여 관측통행량을 이용하여 추정하는 방법을 제안하였다.

• Journal of Korean Society of Transportation
• /
• v.2 no.1
• /
• pp.33-68
• /
• 1984

수요감응교통체계는 승객들의 통행요구에 따라 보다 신속하고 효율적으로 안락하고 편리하게 경제적으로 교통서비스를 제공하는 것이다. 특히 기존의 공공교통수단이 미치지 못하는 저밀도 도시 지역의 통행수요를 만족시키는데 좋은 수단으로써 관심의 대상이 되고 있다. 즉 리무진 같은 소형차량을 이용하여 승객의 통행요청에 따라 개인적인 door-to-door 서비스를 제공하는 것이다. 본연구는 수요감응교통체계의 대안으로서 도시 서비스에 있어서 고정.노선변경승객 써비스에 대한 $\ulcorner$스케쥴 알고리즘$\lrcorner$을 개발하는데 목표를 둔바 목적함 수는 Waiting time, Riding time,Scheduled vehicle의 노선용량제한등과 같은 승객써비스 시 간제약에 대해서 각기 개별차량 여행과의 차를 극대화하여 보았다. 사용자중심 Sub-program과 PASS의 두 Sub-program으로 구성된 Simulation 모형을 활용할 경우 어떠 한 도시 써비스지역에서의 고정노선 혹은 변경노선 각각에 대해서 임시적인 차량운행의 감 응식 효율 증진에 크게 기여할 수 있는 것으로 나타났다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.214-215
• /
• 2013

The main criteria for objective measure of the level of transportation service is travel time and delay time. In this paper, the level of service is measured by using moving vehicles method. Through this, we get the hourly traffic volume, the average travel time, space average speed, etc. In addition, we get the density of traffic.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2014.01a
• /
• pp.105-106
• /
• 2014

본 논문에서는 통행 시간의 측정 방법 중 하나인 CCTV를 활용한 주행 차량 조사법을 이용하여 교통량을 측정한다. 교통망의 서비스 수준을 측정하는 주요 기준인 통행 시간과 지체 시간에 대하여 알아본다. 신호등 간격이 넓어서 연속적인 교통류 특성을 갖는 곳에서 측정을 하도록 한다. 반대편의 교통류가 충분히 식별 가능한 구간이어야 하고, 구간의 끝부분에서는 유턴이 가능해야 한다. 이 방법은 측정차량의 운전수만 있으면 CCTV와 프로그램이 알아서 측정하고, 시간, 거리, 교통량을 기록할 수 있는 장비도 필요 없다.

• Journal of Korean Society of Transportation
• /
• v.23 no.8 s.86
• /
• pp.181-191
• /
• 2005

This study developed an algorithm for real-time signal control based on the detection system that can collect sectional travel time. The signal control variable is maximum queue length per cycle and this variable has a sectional meaning. When a individual vehicle pass through the detector, we can gather the vehicle ID and the detected time. Therefor we can compute the travel time of an individual vehicle between consecutive detectors. This travel time informations were bisected including the delay and not. We can compute queue withdrawing time using this bisection and the max queue length is computed using the deterministic delay model. The objective function of the real-time signal control aims equalization of queue length for all direction. The distribution of the cycle is made by queue length ratios.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.15 no.2
• /
• pp.98-106
• /
• 2011

The deck of steel box girder bridges is composed of deck plate, longitudinal rib, and transverse ribs. The orthotropic steel decks have high possibility to fatigue damage due to numbers of welded connection part, the heavy contact loadings, and the increase of repeated loadings. Generally, the local stress by the repeated loadings of heavy vehicles causes the orthotropic steel deck bridge to fatigue cracks. The increase of traffic volume and heavy vehicle loadings are promoted the possibility of fatigue cracks. Thus, it is important to exactly evaluate the structural behavior of bridge considering the contact loading area of heavy vehicles and real load patterns of heavy trucks which have effects on the bridge. This study estimated the effect of contact area of design loads and real traffic vehicles through the finite element analysis considering the real loading conditions. The finite element analysis carried out 4 cases of loading patterns in the orthotropic steel deck bridge. Also, analysis estimated the influence of contact area of real truck loadings by the existence of diaphragm plate. The result of finite element analysis indicated that single tire loadings of real trucks occurred higher local stress than one of design loadings, and especially the deck plate got the most influence by the single tire loading. It was found that the diaphragm attachment at joint part of longitudinal ribs and transverse ribs had no effects on the improvement of structural performance against fatigue resistance in elastic analysis.

• Journal of Korean Society of Transportation
• /
• v.24 no.2 s.88
• /
• pp.157-168
• /
• 2006

Spatial detection system such as AVI, GPS, and Beacon etc. can provide spatial travel time only after a vehicle Passes through a road section. In this context, majority of the existing studies on the link travel time estimation area has focused on the arrival time-based link travel time estimation. rather than departure time-based link travel time estimation. Even if some of the researches on this area have developed departure time-based link travel time estimation algorithms, they are limited in that they are not applicable in a real-time mode. The objective of this study is to develop an departure time-based link travel time estimation algorithm which is applicable in a real-tine mode. Firstly, this study discussed the tradeoff between accuracy and timeliness of the departure time-based on-line link travel time estimates. Secondly, this study developed an departure time-based on-line link travel time estimation algorithm which utilizes the Baysian inference logic. It was found that the proposed approach could estimate departure time-based link travel times in a real-time context with an acceptable accuracy and timeliness.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.10 no.6
• /
• pp.63-73
• /
• 2011

Travel speed is an important parameter for measuring road traffic. UTIS(Urban Traffic Information System) was developed as a mobile detector for measuring link travel speeds in South Korea. After investigation, we founded that UTIS includes some missing data caused by the lack of probe vehicles on road segments, system failures and etc. Imputation is the practice of filling in missing data with estimated values. In this paper, we suggests a new model for imputing missing data to provide accurate link travel speeds to the public. In the field test, new model showed the travel speed measuring accuracy of 93.6%. Therefore, it can be concluded that the proposed model significantly improves travel speed measuring accuracy.

• Journal of Korean Society of Transportation
• /
• v.21 no.1
• /
• pp.91-102
• /
• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.