• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.57-66
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• 2012

This study intended to evaluate the operational performance change from the introduction of the bus signal priority system using the field data. To complete the objective, travel time and volume data were collected from the before and after study, then the distribution of individual vehicle's travel time and the difference of travel time and traffic volume were compared respectively. Analysis results showed that no significant volume change was observed from both passenger vehicle and bus for the major and cross streets. It was identified that the quality of travel time distributions of passenger vehicle and bus was improved after introducing the bus signal priority system. In terms of average speed, passenger car in a major direction increased by 6.5% and bus increased by 10.5% in general. Statistical tests showed that those speed differences were statistically significant at the 95% of confidence level. The results of this paper will be a good source for further research in the area of bus signal priority control.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.1-11
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• 2009

TCS Data imply characteristics of traffic conditions. However, there are outliers in TCS data, which can not represent the travel time of the pertinent section, if these outliers are not eliminated, travel time may be distorted owing to these outliers. Various travel time can be distributed under the same section and time because the variation of the travel time is increase as the section distance is increase, which make difficult to calculate the representative of travel time. Accordingly, it is important to grasp travel time characteristics in order to compute the representative of travel time using TCS Data. In this study, after analyzing the variation ratio of the travel time according to the link distance and the level of congestion, the outlier elimination model and the smoothing model for TCS data were proposed. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variation of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.193-204
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• 2022

Smart card data is representative mobility data and can be used for policy development by analyzing public transportation usage behavior. This paper deals with the problem of classifying metro stations using metro usage patterns as one of these studies. Since the previous papers dealing with clustering of metro stations only considered traffic among usage behaviors, this paper proposes clustering considering traffic time as one of the complementary methods. Passengers at each station were classified into passengers arriving at work time, arriving at quitting time, leaving at work time, and leaving at quitting time, and then the estimated shape parameter was defined as the characteristic value of the station by modeling each transit time to Weibull distribution. And the characteristic vectors were clustered using the K-means clustering technique. As a result of the experiment, it was observed that station clustering considering pass time is not only similar to the clustering results of previous studies, but also enables more granular clustering.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.193-198
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• 1999

An asymptotic distribution of the ratio of two normal vectors is estimated. Using the estimated asymptotic distribution, an approximation method to estimate confidence interval of passenger's value of travel time is proposed. As a result of empirical study the 95% confidence interval of value of travel time of home-to-work trips in city of Seoul is estimated at ￦7341.25$\pm$1945.05/hr.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.55-67
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• 2002

구간검지체계를 기반으로 한 첨단교통정보제공시스템(Advanced Traveler Information Systems)은 그 기능 수행시 다음의 중요 고려사항을 지닌다. 첫째는 제공 정보의 신뢰성이며, 둘째는 정보수집비용에 관련한 수집자료수의 한계이다. 본 논문에서는 이러한 한계성 극복을 위해 보다 대표성 있는 교통정보 형태의 설정 및 통계적으로 신뢰성 있는 정보산출을 위해 요구되는 적정표본수의 결정에 대한 연구를 수행하였다. 도시고속도로(올림픽대로)와 도시간선도로(천호대로)의 실측 구간통행시간분포 분석결과 단일교차로 구간의 경우 다른 구간들의 단일봉(unimodal)의 정규분포형태와는 다른 두 개의 봉우리를 지닌 분포형태(bimodal)가 나타났다. 따라서 이러한 구간은 기존과는 다른 새로운 교통정보 형태가 필요하며, 본 논문에서는 모든 통과차량들의 평균통행시간으로 정의되는 한 개의 대표치가 아닌 신호주기에 의한 정지여부에 따라 분리되는 주행시간과 지체시간 또는 주행속도와 통행속도 개념의 세분화된 정보형태를 설정하였다. 또한 중심극한정리를 기초로 한 통계적인 표본수 결정식을 이용하여 설정된 신뢰수준 하에서의 정보산출을 위해 요구되는 적정 표본수를 산출하였다. 그 결과, 교통이 혼잡할수록 요구되는 표본수는 적어지는 것으로 나타났다. 우선 적정 표본수 만큼의 표본추출을 하고 제안된 정보산출 방법에 의해 교통정보를 산출한 후 실측치와의 오차를 비교하였다. 그 결과 산출된 교통정보는 신뢰수준 95%와 허용오차 5㎞/h를 만족하였다. 다음으로 구간검지체계를 이용하여 정보를 산출하는 타시스템 교통정보와의 오차율을 비교하였다. 그 결과, 실측치와 본 연구의 산출방법에 의한 교통정보, 로티스교통정보 및 차량번호판 인식시스템의 교통정보와의 비교 결과 제안된 교통정보형태의 타당성을 볼 수 있었다.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.143-155
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• 2009

A dynamic traffic assignment (DTA) has recently been implemented in many practical projects. The core of dynamic model is the inclusion of time scale. If excluding the time dimension from a DTA model, the framework of a DTA model is similar to that of static model. Similar to static model, with given exogenous travel demand, a DTA model loads vehicles on the network and finds an optimal solution satisfying a pre-defined route choice rule. In most DTA models, the departure pattern of given travel demand is predefined and assumed as a fixed pattern, although the departure pattern of driver is changeable depending on a network traffic condition. Especially, for morning peak commute where most drivers have their preferred arrival time, the departure time, therefore, should be modeled as an endogenous variable. In this paper, the authors point out some shortcomings of current DTA model and propose an alternative approach which could overcome the shortcomings of current DTA model. The authors substitute a traditional definition for time-dependent OD table by a new definition in which the time-dependent OD table is defined as arrival time-based one. In addition, the authors develop a new DTA model which is capable of finding an equilibrium departure pattern without the use of schedule delay functions. Three types of objective function for a new DTA framework are proposed, and the solution algorithms for the three objective functions are also explained.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.64-79
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• 2023

This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.225-237
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• 1998

본 연구의 목적은 가로망의 구조 및 통행수요의 변화에 따라 통행 중 교통정보제공의 효과가 어떻게 달라지는가를 모의실험을 통하여 분석하고자 하는 것이다. 이를 위하여 본 연구에서는 실제의 대규모 가로망에 대하여 적용할 수 있는 통행배정기법을 제안하였다. 제안된 모형은 시간의 흐름에 따른 가로망의 상태를 고려하여 통행을 배정하는 방법으로 $\ulcorner$시간종속적 통행배정$\lrcorner$이라 명하였다. 본 연구에서는 가로망 형태(격자형 및 방사환상형), 가로망 크기, 통행수요의 지역별 분포, 그리고 교통혼잡정도에 따라 각각 시나리오를 작성하고, 각 시나리오에 대하여 모의실험 및 사례연구(노드 348개, 링크 1179개)를 통해 정보를 받는 차량의 비율에 따른, 그리고 정보를 제공하는 빈도에 따른 통행중 교통정보제공에 대한 효과를 분석하였다. 연구 결과, 모의실험에서는 정보를 받는 차량의 비율이 30%~70% 구간에서 14%까지의 총체계비용의 감소효과가 나타났으며, 가로망의 규모가 클수록, 혼잡이 심할수록, 그리고 대안도로가 많을수록 교통정보제공의 효과는 커지는 것으로 분석되었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1115-1122
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• 2013

Recently the demands for traffic information tend to increase, and travel time might one of the most important traffic information. To effectively estimate exact travel time, highly reliable traffic data collection is required. BIS(Bus Information System) data would be useful for the estimation of the route travel time because BIS is collecting data for the bus travel time on the main road of the city on real-time basis. Traditionally use of BIS data has been limited to the realm of bus operating but it has not been used for a variety of traffic categories. Therefore, this study estimates a route travel time on road networks in urban areas on the basis of real-time data of BIS and then eventually constructs regression models. These models use an explanatory variable that corresponds to bus travel time excluding service time at the bus stop. The results show that the coefficient of determination for the constructed regression model is more than 0.950. As a result of T-test performance with assistance from collected data and estimated model values, it is likely that the model is statistically significant with a confidence level of 95%. It is generally found that the estimation for the exact travel time on real-time basis is plausible if the BIS data is used.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.10-21
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• 2013

This study suggested combined filtering model to eliminate outlier travel time data in transportation information system, and it was based on Median Absolute Deviation and Voting Rule. This model applied Median Absolute Deviation (MAD) method to follow normal distribution as first filtering process. After that, Voting rule is applied to eliminate remaining outlier travel time data after Median Absolute Deviation. In Voting Rule, travel time samples are judged as outliers according to travel-time difference between sample data and mean data. Elimination or not of outliers are determined using a majority rule. In case study of national highway No. 3, combined filtering model selectively eliminated outliers only and could improve accuracy of estimated travel time.