• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.60-67
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• 2016

In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.63-75
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• 2018

A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.179-187
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• 2009

This study develops a real-time signal control algorithm based on sectional travel times and includes a field test and evaluation. The objective function of the signal control algorithm is the equalization of delay of traffic movements, and the main process is calculating dissolved time of the queue and delay using the sectional travel time and detection time of individual vehicles. Then this algorithm calculates the delay variation and a targeted red time and calculates the length of the cycle and phase. A progression factor from the US HCM was applied as a method to consider the effect of coordinating the delay calculation, and this algorithm uses the average delay and detection time of probe vehicles, which were collected during the accumulated cycle for a stabile signal control. As a result of the field test and evaluation through the application of the traffic signal control algorithm on four consecutive intersections at 400m intervals, reduction of delay and an equalization effect of delay against TOD control were confirmed using the standard deviation of delay by traffic movements. This study was conducted to develop a real-time traffic signal control algorithm based on sectional travel time, using general-purpose traffic information detectors. With the current practice of disseminating ubiquitous technology, the aim of this study was a fundamental change of the traffic signal control method.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.715-727
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• 2002

The travel time of a flood through a river reach can be estimated by dividing the river length by the mean velocity with which the flood passes downstream. It is closely related to storage constant for the watershed routing of a flood. There are so many empirical formulas available for the estimation of travel time but the results computed generally show great different depending on individual formulas. In the present study, the mean velocity data computed in the process of water surface profile computation for a probability flood through more than 100 different river reaches were collected along with the mean river bed slope of each river reach. And then, a regression analysis is made between the mean river bed slope and the mean velocity, which showed a wide scatter along the mean regression curve, which appears to be due to the different in the magnitude of probability rainfall and size of watershed area. Therefore, methods have been developed to remove the effect of these factors and generalized empirical equation is proposed to relate the mean velocity to mean river bed slope of a reach. Hence, if the mean river bed slope of a river reach is estimated from the longitudinal river profile, the mean velocity can be computed by the generalized equation along with the probability rainfall and watershed area of the river reach under consideration, which leads to the estimation of travel time through a river reach.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.113-129
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• 1999

It is widely recognized that the value of travel time (VOT) plays an important role both in choosing the transportation alternatives on an individual level, and in analyzing and evaluating transportation plans and other public policy makings on a collective level. There is, however, a great deal of difficulties to correctly estimate the VOT. In addition, although there are lots of methods to estimate the VOT so for, not many recommendations have been presented to reflect the localities associated with the VOT derivation in Korea. This study aims at deriving the VOT for different trip purposes and travel modes with their significances tested. To accomplish this purposes, a logit-based travel mode choice model based on revealed preference (RP) data has been formulated, calibrated using the discrete choice model of LIMDEP package for various trip purpose models. For each trip purpose and travel mode, the VOT has been calculated along with the significance testing of the derived VOTs. From the results given in this research, the VOTs for different purposes and modes are identified different, and they are statistically significant. The updated results here in this paper may be a yardstick in evaluating the transportation plans and policies by providing more detailed VOT information for different categories, especially in urban context.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.29-44
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• 2009

A variety of research efforts, using advanced wireless communication technologies, have been made to develop more reliable traffic information system. This study presents a novel decentralized traffic information system based on vehicle infrastructure integration (VII). A major objective of this study was also to devise a methodology for determining appropriate spacing of roadside equipment (RSE) to fully exploit the benefits of the proposed VII-based traffic information system. Evaluation of travel time estimation accuracy was conducted with various RSE spacings and the market penetration rates of equipped vehicle. A microscopic traffic simulator, VISSIM, was used to obtain individual vehicle travel information for the evaluation. In addition, the ANOVA tests were conducted to draw statistically significant results of simulation analyses in determining the RSE spacing. It is expected that the proposed methodology will be a valuable precursor to implementing capability-enhanced next generation traffic information systems under the forthcoming ubiquitous transportation environment.

• 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.27 no.2
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• pp.47-56
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• 2009

Effective detection and correction of outliers of raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning system (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposed a locally weighted regression (LWR) based filtering method for individual vehicle speed data. An important feature of this study was to propose a technique to generate synthetic outliers for more systematic evaluation of the proposed method. It was identified by performance evaluations that the proposed LWR-based method outperformed an exponential smoothing. The proposed method is expected to be effectively utilized for filtering out raw individual vehicle speed data.

• Journal of English Language & Literature
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• v.53 no.2
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• pp.261-280
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• 2007

This paper attempts to examine how woman's role defined by the public discourse took issue with private desires of an individual woman in Tabitha Gilman Tenney's Female Quixotism (1801). Tenney borrows and transforms the ideas of quixotism and picaresque from Don Quixote, which involve an inherent paradox in the post-Revolutionary America. The Republican Ideology emphasized women's crucial role as guardians of family virtue and molders of republican citizens. Therefore, women were not allowed to travel outside of the domestic space as freely as a male picaro could do. In fact, the"adventures"depicted in the novel are constituted of a series of courtship in which Dorcasina, the heroine, unceasingly tries but fails to find a husband fit for her romantic idea about love and marriage formed by novel reading. However, the process shows that a variety of socially disadvantaged groups as well as women were excluded from the public space of the post-Revolutionary America. This half-a-century quest does not end with a conventional happy marriage, but Dorcasina finds herself a disillusioned old maid, resigned to a life of charity. Yet the ending exposes social contradictions inherent in early Republic of America, by showing how an individual woman's life was prescribed and limited by the dominant public discourse.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.71-79
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• 2005

Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.