• 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.29 no.6
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• pp.7-16
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• 2011

This study investigates the degree of dependency on freeways when auto travelers make route choices in the Seoul Metropolitan Area. The investigation is conducted based on aggregated auto trip data, defining the degree of dependency as the proportion of auto trips selecting freeways in their travel paths. The analyses reveal that the trips departing from the areas with higher accessibility to freeways tend to exhibit higher dependency on freeways. In addition, the dependency is significantly affected by the travel time differences between two paths including and excluding freeways, respectively. The number of service interchanges was found to be one of significant factors for trips to Incheon and Gyenggi areas. The finding indicates that the factors affecting the degree of dependency on freeways may vary depending on the areas' characteristics. The findings would enhance the understanding of drivers' route choice behavior in Seoul at an aggregate level.

• 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.

• 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.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.481-498
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• 2017

Travel time reduction benefit is the most important benefit item in the feasibility study of transportation infrastructure investment projects and calculated by using the value of travel time. The current feasibility study guideline (5th edition) calculate the value of non-business ravel time in a metropolitan area, using the ratio of the value of non-business travel time to business travel time calculated based on the nationwide inter-regional traffic survey data of 1999. The characteristics of metropolitan trips are different from those of nationwide regional trips. Metropolitan trips have frequent transfers between multiple public transits and long-time commuter trips. Therefore, this research aims to calculate the value of travel time reflecting traffic characteristics in a metropolitan area by improving the limitation of current calculation methods. To reflect these characteristics, this research extracts commuter trips from non-business trips and calculates the value of travel time for commuter trips. The results of the likelihood ratio test for the commuter trip model and the non-business trip model are found to be statistically significant. An integrated public transportation model was also estimated in this study to reflect the trip conditions of the Seoul metropolitan area integrated fare system. The results of comparing coefficients between bus and subway in the integrated public transit model indicated that there were no statistically significant differences between the two modes.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.83-92
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• 1998

서울과 일산 신도시의 출근통행 교통수단 선택모형을 구축하고, 두 도시간 수단선택행태를 분석.비교하였다. 분석을 위한 자료로는 1996년 서울시에서 수행한 가구통행실태조사자료를 이용하였으며, 수단선택모형으로는 다항로짓모형을 사용하였다. 두 지역 출근통행 수단선택모형의 모형구조상의 차이 및 모형의 지역간 이전가능성을 분석하였고, 출근통행의 시간가치 및 탄력성을 분석하고 비교하였다. 통계적 검증의 결과 출근통행의 수단선택에 있어서, 모형구조적 측면에서나 선택행태적 측면에서 수단 선택모형의 두 도시간 이전은 불가능한 것으로 나타났다. 서울의 출근통행의 시간가치가 일산보다 전반적으로 큰 것으로 분석되었고, 특히 서울의 경우, 택시이용자의 시간가치가 자가용 이용자의 시간가치보다 큰 것으로 나타났다. 두 도시 모두 통행시간에 대한 탄력성 통행비용에 대한 탄력성보다 전반적으로 크며, 버스와 지하철간의 통행시간에 대한 교차탄력성이 매우 높은 것으로 분석되었다.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.75-88
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• 1998

서울과 일산 신도시의 출근통행 교통수단 선택모형을 구축하고, 두 도시간 수단선택형태를 분석.비교하였다. 분석을 위한 자료로는 1996년 서울시에서 수행한 가구통행실태조사자료를 이용하였으며, 수단선택모형으로는 다항로짓모형을 사용하였다. 두 지역 출근통행 수단선택모형의 모형구조상의 차이 및 모형의 지역간 이전가능성을 분석하였고, 출근통행의 시간가치 및 탄력성을 분석하고 비교하였다. 통계적 검증의 결과 출근통행의 수단선택에 있어서, 모형구조적 측면에서나 선택행태적 측면에서 수단선택모형의 두 도시간 이전은 불가능한 것으로 나타났다. 서울의 출근통행의 시간가치가 일산보다 전반적으로 큰 것으로 분석되었고, 특히 서울의 경우, 택시이용자의 시간가치가 자가용 이용자의 시간가치보다 큰 것으로 나타났다. 두 도시 모두 통행시간에 대한 탄력성 통행비용에 대한 탄력성보다 전반적으로 크며, 버스와 지하철간의 통행시간에 대한 교차탄력성이 매유 높은 것으로 분석되었다.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.57-66
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• 2003

Because the Logit model easily calculates probabilities for choice alternatives and estimates parameters for explanatory variables, it is widely used as a traffic mode choice model. However, this model includes an assumption which is independently and identically distributed to the error component distribution of the mode choice utility function. This paper is a study on the estimation of the Heteroscedastic Logit Model. which mitigates this assumption. The purpose of this paper is to estimate a Logit model that more accurately reflects the mode choice behavior of passengers by resolving the homoscedasticity of the model choice utility error component. In order to do this, we introduced a scale factor that is directly related to the error component distribution of the model. This scale factor was defined so as to take into account the heteroscedasticity in the difference in travel time between using public transport and driving a car, and was used to estimate the travel time parameter. The results of the Logit Model estimation developed in this study show that Heteroscedastic Logit Models can realistically reflect the mode choice behavior of passengers, even if the difference in travel time between public and private transport remains the same as passenger travel time increases, by identifying the difference in mode choice probability of passengers for public transportation.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.1-16
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• 2018

Changes in the life style might vary trip purposes, ultimately leading to the change in the travel behavior. Therefore, this study analyzed the factors affecting travel time change by using the time use survey data in Seoul, surveyed by the Statistics Korea in 1999~2014. We developed multiple linear regression models for travel time, considering individual, household and time-related variables as independent variables. The models were separately estimated weekday and weekend. the model results show that the household, individual, and time related variables have an significant effect on the travel time. In addition, travel time is more influenced by individual characteristics thn household ones. Each activity time positively affects the travel time, indicating that travel is derived demand. The variable that have the greatest influence on the travel time is the activity time for leisure.