• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.631-638
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• 2023

This paper is to introduce methodologies of travel time reliability evaluation using daily traffic volumes. The methodologies include desirable speed concept, the relation between averaged daily speeds and daily traffic volumes, the standardized way in integration of travel time deviations obtained from continuous highway sections. The study began with traffic data collection from a freeway line with long lasting congestion. And then, provided establishment of the relation between averaged daily speeds and daily traffic volumes, and usability of Point estimate method (PEM) to integrate travel time deviations of sections. Based on the relation between averaged daily speeds and daily traffic volumes, it is identified that travel time reliability begins to decrease around LOS (Level of Service) C even before LOS D or F. It may be concluded that travel time reliability could be evaluated based on daily traffic volumes in highway sections using standardized PEM. The methodologies introduced in the paper, could be useful in practicing evaluation of travel time reliability during the works of highway operation or highway planning.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.68-79
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• 2010

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in snowing days of 1998-2008. We compare the normal travel patterns with those of snowing days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in snowing days as we expect, and also show different travel patterns for weekday and weekend.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.119-128
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• 2008

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in rainy days of 2006. We compare the normal travel patterns with those of rainy days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in rainy days as we expect, and also show different travel patterns for weekday and weekend.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.174-176
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• 2012

도서 여행객 이용실적을 월별, 일반인/도서민, 항로별로 살펴보고, 도서 여행객의 이동 목적 및 접근수단을 분석하였다. 도서이용객들의 일통행량을 터미널별 평일 및 주말로 구분하여 각각 일반/도서민이 이용하는 비율을 분석하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.61-70
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• 2001

The origin and destination(O-D) matrix is one of the most important elements in transportation planning process. Traditionally, transport planners survey the O-D movements in order to estimate the O-D matrix. Even though the cost of the O-D survey requires high amounts of resources, the accuracy is relatively low. Therefore, many researchers have studied the estimation of the O-D matrix for automobile from traffic counts. however, there is a little attention for the application on the transit O-D matrix estimation from traffic counts. The objective of this study is therefore the estimation of the transit O-D matrix from traffic counts using Gradient method. which is verified by the reliability analysis using a contrived small example network.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.131-141
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• 2008

The objective of this study is to propose methods for determining optimal representative value and the optimal size of historical data for reliable travel time forecasting. We selected values with the smallest mean of forecasting errors as the optimal representative value of travel time pattern data. The optimal size of historical data used was determined using the CVMSE(Cross Validated Mean Square Error) method. According to the results of applying the methods to point vehicle detection data of Korea Highway Corporation, the optimal representative value were analyzed to be median. Second, it was analyzed that 60 days' data is the optimal size of historical data usedfor travel time forecasting.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.183-192
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• 2012

This study analyzes the travel behavior for short-term demand forecasting model of KTX. This research suggests the following. First, the outlier criteria is considered to appropriate twice the standard deviation of the traffic. Second, the result of a homogeneity test using ANOVA analysis has been divided into weekdays(Mon Thu and weekends(Fri Sun). Third, a cluster analysis for O/D pairs using trip frequency, traffic averages and th distance between stations was performed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.709-716
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• 2006

The rapid changes of family structure such as singles, working couples and so on have effects on a travel behaviour. One of the characteristics from this is the increasing portion of trip-chain, in which plural activities were conducted in a "single outgoing" travel. Therefore travel must be considered as location change to conduct various activities instead of pursuing single travel purpose. This paper specifies a behavioral homogeneous person group by a job, a possession of cars. Based on this classification of person groups and their activity diary, the sequence, time and travel mode of activities in a day can be verified. As a case study household survey was conducted in city Kongju. The survey result shows that the classification of behavioral homogeneous person group based on criteria like employment status and car ownership bring a good result to forecast trip generation in traffic zone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.605-612
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• 2019

Traditionally, travel demand forecasts have been conducted based on the data collected by a survey of individual travel behavior, and their limitations such as the accuracy of travel demand forecasts have been also raised. In recent, advancements in information and communication technologies are enabling new datasets in travel demand forecasting research. Such datasets include data from global positioning system (GPS) devices, data from mobile phone signalling, and data from call detail record (CDR), and they are used for reducing the errors in travel demand forecasts. Based on these background, the objective of this study is to assess the feasibility of CDR as a base data for travel demand forecasts. To perform this objective, CDR data collected for Daegu Metropolitan area for four days in April including weekdays and weekend days, 2017, were used. Based on these data, we analyzed the correlation between CDR and travel demand by travel survey data. The result showed that there exists the correlation and the correlation tends to be higher in discretionary trips such as non-home based business, non-home based shopping, and non-home based other trips.