• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.599-617
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• 2006

A network model and a Genetic Algorithm(GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing the non-linear objective functions with the linear constraints. In the model, the flow-conservation constraints of the network are utilized to restrict the solution space and to force the link flows meet the traffic counts. The objective of the model is to minimize the discrepancies between the link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links and the link flows estimated through the traffic assignment using the path flow estimator in the legit-based SUE. In the proposed GA, a chromosome is defined as a vector representing a set of Origin-Destination Matrix (ODM), link flows and travel-cost coefficient. Each chromosome is evaluated from the corresponding discrepancy, and the population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment is applied during the crossover and mutation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.417-424
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• 2006

To get more accurate trip distribution estimation results, this study developed an improved gravity model. Using three different year's O-D table resulted from person trip survey, this study analyzed correlative between basic year's residuals and target year's residuals by gravity model. And resulted that the two have linear correlation. From this, improved gravity model was developed as adding basic year's residual to present gravity model. Developed gravity model was compared to present gravity model by estimation accuracy, and revealed that distributed trips from improved gravity model was more closer to real O-D than distributed trips from present gravity model.

• Journal of Korean Society of Transportation
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• v.18 no.2
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• pp.53-62
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• 2000

현재까지 개발된 교통량 기반 O/D 추정기법들은 추정된 O/D의 신뢰성을 평가하는 기준으로 통계적 오차분석을 통한 참O/D(true O/D)와 추정O/D간의 타이를 분석하는 방법이 주류를 이루었다. 문제는 이러한 오차분석기법들이 현실적인 대규모 교통망상에 적용될 때 탐O/D를 알 수 없을 뿐만 아니라, 알 수 있다고 하더라도 추정된 O/D와의 비교 평가시에 그러한 평가방법으로 추정된 O/D의 신뢰성을 부여하기에는 많은 문제점을 가지고 있다는 점이다. 통행조사에 의한 O/D는 비록 포함되어 있는 정보가 과거의 정보라고 할지라도 현재의 통행흐름에 대하여 가장 많은 정보를 가지고 있다고 할 수 있다. 즉, 선행O/D의 정보를 크게 변화시키지 않으면서도 관측교통량으로 O/D를 추정할 수 있는 방법이 이 관점에서 매우 뛰어난 추정방법이라고 할 수 있다. 이러한 관점에서 본 연구에서는 선행O/D정보 중 통행수요예측시 가장 중요한 지표의 하나인 통행시간빈도분포 (TriP Length Frequency Distribution:TLFD)를 이용하여 추정O/D의 신뢰성 지표로 삼았다. TLFD는 4단계 모형에서 통행분포(trip distribution)시 모형을 정산하는 데 사용되는 방법으로써 죤간 통행시간을 단위별로 나누어 조사된 통행시간분포와 추정된 O/D의 통행시간분포가 유사한 지를 살피는 방법이라고 할 수 있다. 조사된 TLFD와 추정O/D의 TLFD가 유사한 모양을 이를 때 추정O/D의 신뢰성이 높다고 인정한다. 또한 TLFD는 전통적으로 조사된 표본O/D를 전 수화하는데 이용되어 그 타당성 또한 많이 검증되어 왔다. 그러나 아직까지 TLFD를 가지고 교통량으로 O/D를 추정하는 모형의 결과를 검증한 연구 결과는 없는 실정이다. 따라서, 본 연구에서는 최종적인 이러한 분석결과를 평가할 수 있을 뿐 아니라, 평가된 지표가 신뢰할 만한 수준이 아니라면, 추정된 결과를 보정할 수 있는 가능성을 제시하고자 한다.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.43-59
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• 2012

It is generally assumed about trip distribution estimation model that growth factor model's estimation accuracy is higher than that of other models in short-term and that gravity model's estimation accuracy is higher than that of other models in long-term. For validation of such assumptions, this study compares estimation accuracies of each estimation model using 3year(1988, 1992, 2004) O-D tables from Daegu city. Each estimation model's accuracy were compared by mid-size and large-size zone as well as short-term and long-term target years. The results show that the trip distribution estimation model selection by usual assumption is not always right.

• Journal of the Korean Regional Science Association
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• v.31 no.1
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• pp.21-42
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• 2015

This paper investigates whether urban expansion and the vitalization of the local economy can be achieved through new city development. The results show that regardless of the starting point (origin) or destination point, traffic increases closer to the origin for the purpose of transportation and decreases farther from the origin. However, traffic tends to increase in districts 20 to 40 km away from the origin. Hence, building a new city in this district may be effective in terms of geography and functionality.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.372-375
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• 2010

보안등은 주택가 골목에 안전을 위해 설치하는 중요한 설비로서, 도로 폭이 12m 이하인 장소에 설치된다. 그러내 통행 인구가 없어도 야간시간 내내 점등되고 있기에 낭비되는 전력량이 상당하다. 적외선센서가 부착된 보안등을 교체하게 되면 보행자의 움직임을 통해 일정시간 점등이 되고 이동체가 없을 때는 소등이 되어 전기에너지의 소비를 상당히 줄일 수가 있어 온실가스저감에 기여할 수 있다. 본 논문에서는 적외선센서 보안등의 최적 작동시간을 추적하기 위해 보행자의 통행 분포를 알아보고자 연구지역인 경북대 캠퍼스 내에서 사계절 중 여름철 야간 보행자의 통행패턴을 현장조사하여 분석하였다. 이를 통해 시간별, 공간별 분포 특성을 파악하고 도식화하여 보행자의 통행분포 특성을 파악함으로써 보안등의 작동시간 추적이 가능하였다.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.41-48
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• 2020

In this paper, a dynamic prediction algorithm using the cumulative distribution function for traffic volume is presented as a new method for predicting highway traffic rate more accurately, where an approximation function of the cumulative distribution function is obtained through numerical methods such as natural cubic spline interpolation and Levenberg-Marquardt method. This algorithm is a new structure of random number generation algorithm using the cumulative distribution function used in financial mathematics to be suitable for predicting traffic flow. It can be confirmed that if the highway traffic rate is simulated with this algorithm, the result is very similar to the actual traffic volume. Therefore, this algorithm is a new one that can be used in a variety of areas that require traffic forecasting as well as highways.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.25-36
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• 2005

In this study, we suggested a new approach method forecasting distribution demand of urban rail transit usign fuzzy control, with intend to reflect irregularity and various functional relationship between trip length and distribution demand. To establish fuzzy control model and test this model, the actual trip volume(production, attraction and distribution volume) and trip length (space distance between a departure and arrival station) of Daegu subway line 1 were used. Firstly, usign these data we established a fuzzy control model, nd the estimation accuracy of the model was examined and compared with that of generalized gravity model. The results showed that the fuzzy control model was superior to gravity model in accuracy of estimation. Therefore, wwe found that fuzzy control was able to be applied as a effective method to predict the distribution demand of urban rail transit. Finally, to increase the estimation precision of the model, we expect studies that define membership functions and set up fuzzy rules organized with neural networks.