• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.147-155
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• 2005

The purpose of this paper is to develop a method for estimation of reliable path-travel time using data obtained from the toll collection system on freeways. The toll collection system records departure and arrival time stamps as well as the identification numbers of arrival and destination tollgates for all the individual vehicles traveling between tollgates on freeways. Two major issues reduce accuracy when estimating path-travel time between an origin and destination tollgate using transaction data collected by the toll collection system. First, travel time calculated by subtracting departure time from arrival time does not explain path-travel time from origin tollgate to destination tollgate when a variety of available paths exist between tollgates. Second, travel time may include extra time spent in service and/or rest areas. Moreover. ramp driving time is included because tollgates are installed before on-ramps and after off-ramps. This paper describes an algorithm that searches for arrival time when departure time is given between tollgates by a Progressive Iterative Forward and Backward (PIFAB) search method. The algorithm eventually produces actual path-travel times that exclude any time spent in service and/or rest areas as well as ramp driving time based on a link-based procedure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.457-465
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• 2018

This study proposes a novel approach to explore a "travel time budget (TTB)" using a mobile phone signaling data (MPSD), which are passively generated between a mobile phone and a base station. The data analyzied in this study were provided from KT for 8 days (from May 19 to 26 in 2016). They were about 45 million signals passively generated from users whose stay area during night was classified as three areas in Mapo-gu, Seoul and in the city of Sejong. The estmation of TTB was implemented with various pre-processing techniques on the MPSD data in a data-driven analysis. As a result, the TTBs of Mapo-gu, Seoul and Sejong were 82.94 and 80.70 minutes, respectively. The results in this study were also compared with those based on the traditional methods. The authors expect that this result will help transport experts improve the use of MPSD.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.565-571
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• 2006

This study aimed to analyze access mode choice behavior for KTX Passengers. To fulfill the aims of this study, Dong-Daegu Station was selected as a station for a case study. This study takes place in two stages. These are (i) descriptive statistical analysis of transportation status before and after introduction of the KTX, (ii) empirical model estimation for analyzing access mode choice behavior. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The data was collected from a sample of 1,800 individuals. The survey data includes the information on travel from Dong-Daegu station to Seoul. From descriptive statistical analysis of transportation status before and after introduction of the KTX, it is found that revealed demand of the KTX is lower than that expected. Moreover, it is found that the low demand of the KTX stems from high cost for the KTX itself and inconvenience( including travel time and cost) of access mode. In order to analyze mode choice behavior for accessing Dong-Daegu station, multinomial logit model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the access mode choice, were considered. From the empirical model estimation, it si found that access travel time and access travel cost are significant in choosing access mode. Given the empirical evidence, we see that improvement of access transportation system for Dong-Daegu station is very important for enhancing the use of KTX.

• International Journal of Highway Engineering
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• v.18 no.2
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• pp.91-101
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• 2016

PURPOSES : The aim of this study was to compare the performance of the QUEENSOD method and the gravity model in estimating Origin-Destination (O/D) tables for a large-sized microscopic traffic simulation network. METHODS : In this study, an expressway network was simulated using the microscopic traffic simulation model, VISSIM. The gravity model and QUEENSOD method were used to estimate the O/D pairs between internal and between external zones. RESULTS: After obtaining estimations of the O/D table by using both the gravity model and the QUEENSOD method, the value of the root mean square error (RMSE) for O/D pairs between internal zones were compared. For the gravity model and the QUEENSOD method, the RMSE obtained were 386.0 and 241.2, respectively. The O/D tables estimated using both methods were then entered into the VISSIM networks and calibrated with measured travel time. The resulting estimated travel times were then compared. For the gravity model and the QUEENSOD method, the estimated travel times showed 1.16% and 0.45% deviation from the surveyed travel time, respectively. CONCLUSIONS : In building a large-sized microscopic traffic simulation network, an O/D matrix is essential in order to produce reliable analysis results. When link counts from diverse ITS facilities are available, the QUEENSOD method outperforms the gravity model.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.45-52
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• 2010

The relationship between climate changes and transportation could be separated by two approaches. One of methods was to find how climate changes affected transportation, and the other way was how transportation affected climate changes. In this study, we reported from the former standpoint, how climate changes affected transportation fields. When there is a lot of snowfall in Seoul, it starts ripple effect through the travel patterns. They can be explained by travel time and operating cost. The travel costs were calculated in this paper for analysing the effect of disbenefit by climate changes. Snow Melting System was also studied for relieving negative influences under the unpredictable weather condition. As a result, the system was effective for minimizing disbenefit by climate changes.

• Journal of Ecology and Environment
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• v.30 no.2
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• pp.201-207
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• 2007

Researchers have used a variety of methods to measure patterns of animal movement, including the use of spatial data (mapping the position of a moving animal at specified intervals) and direct estimation of travel path length by pacing under a moving animal or group. I collected movement data from five groups of siamangs (Symphalangus syndactylus) using two different methods concurrently to estimate the effects of the method of data collection on estimates of daily path length (DPL). Estimates of DPL produced from spatial data collected at 15-minute intervals were 12% lower than estimates of DPL produced by pacing under the traveling animal. The actual magnitude of the difference was correlated with the travel distance, but there was no correlation between the proportional difference and the travel distance. While the collection of spatial data is generally preferable, as spatial data permit additional analyses of patterns of movements in two or three dimensions, the relatively small difference between the DPL's produced using different methods suggests that pacing is an acceptable substitute where the collection of spatial data is impractical. I also subsampled the spatial data at increasing time intervals to assess the effect of sampling interval on the calculation of daily path lengths. Longer sampling intervals produced significantly shorter estimates of travel paths than shorter sampling intervals. These results suggest that spatial data should be collected at short time intervals wherever possible, and that sampling intervals should not exceed 30 minutes. Researchers should be cautious when comparing data generated using different methods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.1
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• pp.26-33
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• 2012

Competition between air transportation and railways has grown fiercer in major countries around the world with the rise of high-speed railways. In South Korea, air passenger travel has been rapidly decreasing since the initial launch of the Seoul-Pusan KTX line in 2004 and second opening that followed in 2010. Further expansion of the high-speed railway is expected. At present, research efforts to verify the validity of constructing an underwater express railway tunnel between Ho-nam and Jeju Island are taking place. Considering the possible high speed railway connection between Seoul and Jeju Island, this thesis has analyzed the choice behavior of existing passengers of the major and low-cost carriers. For this, Stated Preference (SP) research has been performed for three variables, including fare, travel time and the number of runs, to estimate the substitution rate of each of the three variables. Binomial Logit Model has been estimated with the obtained data. The estimation of the model has found that airline passengers of major and low-cost carriers are willing to pay approximately 7,200 KRW and 5,000 KRW, respectively, to reduce travel time by one hour. If the number of runs in one day increases, it has been estimated that the passengers are willing to pay additional fares of about 390 KRW and 30 KRW, respectively. On the other hand, the substitution rate between the number of runs and the travel time was found to be somewhat insignificant. If the construction of the Seoul-Jeju line progresses in the future, this study could be used as preliminary data for determining fares, travel time and the number of runs.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.89-102
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• 2006

The purpose of this paper is to develop a dynamic OD estimating model to overcome the limitation of depicting teal situations in dynamic simulation models based on static OD trip. To estimate dynamic OD matrix we used the hybrid discrete choice model(called the 'Demand Simulation Model'), which combines travel departure time with travel mode and travel path. Using this Demand Simulation Model, we deduced that the traveler chooses the departure time and mode simultaneously, and then choose his/her travel path over the given situation In this paper. we developed a hybrid simulation model by joining a demand simulation model and the supply simulation model (called LiCROSIM-P) which was Previously developed. We simulated the hybrid simulation model for dependent/independent networks which have two origins and one destination. The simulation results showed that AGtt(Average gap expected travel time and simulated travel time) did not converge, but average schedule delay gap converged to a stable state in transportation network consisted of multiple origins and destinations, multiple paths, freeways and some intersections controlled by signal. We present that the hybrid simulation model can estimate dynamic OD and analyze the effectiveness by changing the attributes or the traveler and networks. Thus, the hybrid simulation model can analyze the effectiveness that reflects changing departure times, travel modes and travel paths by demand management Policy, changing network facilities, traffic information supplies. and so on.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.193-201
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• 2011

The provision of traffic information plays an important role in increasing social benefit not only by saving travel time for individuals but also by improving the efficiency of road operation. VMS(Variable Message Sign) helps on-wheel drivers easily understand the road situation, and also provides real-time traffic information to people on the streets. However, it has not been sufficiently studied on how traffic information based on VMS influences on the drivers' selection of route. This study investigated how drivers use VMS traffic information and how they are satisfied with it. Then, the model of drivers' route selection was specified with the types of traffic information and the expected travel time to examine the influence on the selection of drivers' route. The model was estimated and analyzed in three types according to the condition of detour roads, and the rate of route change and the degree of sensitivity was calculated from the estimation. The results of analysis are as follows. the $1^{st}$ type model showed the 10% of route change for the travel time saving of 5minutes, and the 81.6% of route change for the travel time saving of 20minutes. The $2^{nd}$ type led to the range of route change from 14.2% to 92.7% over the 5 through 20 minutes of travel time saving. The $3^{rd}$ model resulted in the 99.1% of route change. The sensitivity of route change showed the highest for the travel time saving of 11 minutes with the $1^{st}$ type model, 9 minutes with the $2^{nd}$ type model, and 5 minutes with the $3^{rd}$ type model respectively.