• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.217-226
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• 2008

The term, travel-time reliability, refers to variations in journey time that travelers cannot predict. The purpose of this paper is to suggest a standard way to measure travel time reliability. A modified buffer time indicator is proposed. The index is represented by the difference between planned and actual travel times based on lognormal type travel time distribution. Using this framework, a constant function for railways and a negative parabola function for roads are discussed. The model developed is applied to the real data of Korean road and rail usages to empirically verify the methodology proposed. In this process, the unit value of travel time reliability for each group is estimated. The result of this research is expected to be helpful of conducting more cautious economic feasibility studies of transport.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.247-255
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• 2021

Individual passenger transfer information is not included in Seoul metropolitan subway Automatic Fare Collection (AFC) data. Currently, basic data such as travel time and distance are allocated based on the TagIn terminal ID data records of AFC data. As such, knowledge of the actual path taken by passengers is constrained by the fact that transfers are not applied, resulting in overestimation of the transport index. This research proposes a method by which a transit path that connects the TagIn and TagOut terminal IDs in AFC data is determined and applied to the transit index. The method embodies the concept that a passenger's line of travel also accounts for transfers, and can be applied to the transit index. The path selection model for the passenger calculates the line of transit based on travel time minimization, with in-vehicle time, transfer walking time, and vehicle intervals all incorporated into the travel time. Since the proposed method can take into account estimated passenger movement trajectories, transport-related data of each subway organization included in the trajectories can be accurately explained. The research results in a calculation of 1.47 times the values recorded, and this can be evaluated directly in its ability to better represent the transportation policy index.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.1-13
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• 2015

Travellers consider extra travel time to be arriving their destination because of uncertainty of travel. So it is important to make predictable highway by providing information of travel time variability to traveller so as to enhance level of service at highway. In order to make predictable highway, it is necessary to develope measures of travel time variability that travellers can easily understand. Recently advanced country including the United States, travel time variability index are actively studied. In earlier study, 95percentile of travel time is considered to be most important calculation index of travel time variability. In this study, is has focused on the propriety analysis of 95percentile of travel time in domestic transportation environment. Result of analysis, All of measures(80percentile of travel time, 90percentile of travel time, 95percentile of travel time) show the tendency to increase when case of weather factor occur compare to normal condition under LOS A~D. Especially 95percentile of travel time increased sensitively.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.180-191
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• 2020

This study analyzes factors that affect average daily travel time budgets, using the Time Use Survey data from 1999 to 2014 in Seoul. We first developed multivariate regression models for travel time from each year, considering demographic and socio-economic variables as well as non-home activity time. The model results showed that household and personal characteristics and non-home activities significantly affect travel time, and their effects are different over time. In addition, we developed seemingly unrelated regression (SUR) models for time allocation for non-home activity and travel, considering their correlations, and explanatory variables were compared over time. Overall, demographic and socio-economic variables significantly affect travel time as well as non-home activity time.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.7-16
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• 2008

There are unique aspects of truck vehicle movements compared with the personal travel in trip chaining. This paper reports an analysis on the truck vehicle trip chaining which intercity/metropolitan/intraregional trips are classified. Data collected from the travel dairy survey is used the truck trip-chaining analysis. The pattern of trip chaining classes is classified by the GIS mapping based on orgin-destination trip information. The physical index and efficiency index for each trip diary is used to the truck vehicle activity. Truck trips lengths and time differs from its truck type, service type and travel patterns. It is shown that the efficiency of the truck trip chaining depends on vehicle types and its delivery patterns. There are many other topics for research on trip chaining modeling such as the classification of trip chain, time use and mode choice by trip chaining.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. 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 variaty 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.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.103-112
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• 2012

This research introduces a trip generation model reflecting time-series effects derived from a panel analysis with the data collected from the national household trip surveys conducted in 1996, 2002 and 2006. The existing methods are unable to reflect time-series effects from the change of socioeconomic conditions because the parameters applied to the model were basically from the base year of study - the parameter values were unchanged. This study proposes a new trip generation model developed through a panel analysis performed with the data collected from the last three national household trip surveys. From the results, it was found that the number of school trips increases and that the number of shopping trips decreases as time passes. The results showed that there are time-series effects affecting in trip generation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.547-553
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• 2011

This study has redefined the concepts of mobility indexes and potential demand, standards to evaluate areas with the worst public transportation system and applied the relevant indexes to select the areas with the worst public transportation mobility and present a method to set direct public transportation lines between these regions. The mobility indexes and indexes to evaluate potential demand were applied to select the regions with the worst public transportation systems in four metropolitan cities and case studies were carried out on direct lines provided between these regions. The analysis results showed that in public transportation mobility blind spots, public transportation takes much longer than driving an automobile or public transportation services are not provided. In addition, the analysis showed that a direct lines system to solve such worst off regions should be built to have public transportation take as much time as driving an automobile by establishing lines for automobiles only, minimize time lost from hopping up and down a bus and maximize connections.