• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2465-2471
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• 2013

This paper develops a travel time prediction algorithm that can be used for real-time application. The algorithm searches for the most similar pattern in historical travel time database as soon as a series of real-time data become available. Artificial neural network approach is then taken to forecast travel time in the near future. To examine the performance of this algorithm, travel time data from Gyungbu Highway were obtained and the algorithm is applied. The evaluation shows that the algorithm could predict travel time within 4% error range if comparable patterns are available in the historical travel time database. This paper documents the detailed algorithm and validation procedure, thereby furnishing a key to generating future travel time information.

• Health Policy and Management
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• v.8 no.1
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• pp.183-202
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• 1998

This study is to investigate patient's choice of health care and the demand for Korean traditional medicine care in rural areas in 1995. It tried to evaluate the effect of out-of-pocket expenditure, travel time, and waiting time on improving care-seeking and substituting clinical medicine for pharmacy care and Korean traditional medicine care in rural areas. The statistical model of this study is conditional logit to estimate effects of choice-specific and individual-specific characteristics on the choice of type of services. This study used, as explanatory variables, average out-of-pocket payment, travel time, and waiting time of services required to use the services. The model was empirically tested using data from 1995 Korean National Health Survery. The results showed that rural Koreans responded to out-of pocket payment and travel time. Increases of out-of-pocket payment and travel time decreased the probability to choose care in rural Korea. Rural Koreans were more likely to seek care than others with low out-of-pocket payment and travel time. The probability of choosing Korean traditional medicine were higher among the members of the households with higher education level and older persons, while they were lower in the households with large family than others compared with the probabilities of choosing public health facilities. The result of this study implies that policy on use of health care in rural Korea can be focused in managing travel time and out-of-pocket payment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.739-746
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• 2006

The bus probe-based link travel times were more readily available due to bus' fixed route schedule and it was different from that of taxi-based one in its value for the same link. At the same time, the bus-based one showed less accurate information than the taxi-based link travel time, in terms of reliability expressed by 1-RMSE(%) measure. The purpose of this thesis is to develop a heuristic algorithm for mixing both sources-based link travel times. The algorithm used both real-time and historical profile travel times. Real-time source used 4 consecutive periods' average and historical source used average value of link travel time for various congestion levels. The algorithm was evaluated for Seoul urban arterial network 3 corridors and 20 links. The results based on the developed algorithm were superior than the mere fusion based link travel times and the reliability amounted up to 71.45%. Some limitation and future research agenda have also been discussed.

• 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.

• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.166-170
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• 2006

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1873-1879
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• 2014

There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.13-21
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• 2009

The traveler's travel pattern has significantly changed due to the social and economic changes. The travel time among the traveler's pattern is the limited resource. The travelers are trying to maximize the utility of travel with the least travel cost. So, the travelers travel with their own travel time budget in mind, which they can pay or choose to pay for the optimal maximization of the utility of the individuals. This research is to group and extract the specific factors which affect the travel time budget by utilizing the CART analysis method, which enables the analysis of traveler's characteristics and their interrelationship based on the data collected from "2002 Household Travel Practice Research" and then try to derive a model for estimating the traveler’s travel time budget. The result of CART analysis shows that the factors which affect the travel time budget include the traveler's age, size of house, type of house, type of employment, job and relation to the head of household. Considering the affecting factors derived, I developed an estimation model. From that model, we found that the age, size of house and type of house were positively (+) related to the travel time budget while the homeworking people who have less travel frequency as a type of employment were negatively (-) related to it. In particular, from the point of type of job, the housewives, children not yet old enough to attend schools and people who are working in the agricultural, or marine product industries were found to have the negative (-) value while the people who have the administrative, office, management jobs were found to have the positive (+) value.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.34-45
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• 2006

In this study comparison estimates travel times with observed travel time. In generally, peak flood discharges decrease become travel times longer. 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, storage coefficients and lag time but results computed generally show great different depending on individual formulas. When calculated flood discharge depend on the travel times varying the discharge. In this study the Wichun travel time shorter optimization travel time than observed travel time for the rusa and memi. There are showed good results for flood discharges, water level and velocity of the memi at the Younggok.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.14-26
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• 2009

This study presented a novel method to estimate travel times under incident conditions. Predictive travel time information was defined and evaluated with the proposed method. The proposed method utilized individual vehicle speeds obtained from global positioning systems (GPS) and inter-vehicle communications(IVC) for more reliable real-time travel times. Individual vehicle trajectory data were extracted from microscopic traffic simulations using AIMSUN. Market penetration rates (MPR) and IVC ranges were explored with the accuracy of travel times. Relationship among travel time accuracy, IVC ranges, and MPR were further identified using regression analyses. The outcomes of this study would be useful to derive functional requirements associated with traffic information systems under forthcoming ubiquitous transportation environment

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.45-54
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• 2013

Korea Expressway Corporation has been utilizing vehicles equipped with dedicated short range communication (DSRC) based on-board equipment (OBE) for collecting path travel times. A path based method (PBM) estimates the path travel time using probe vehicles traveling whole links on the path, so it is not always possible to obtain sufficient samples for calculating path travel time in the DSRC system. Having this problem in utilizing DSRC for travel time information, this study attempted to estimate path travel time with the help of a link based method (LBM) and examined whether the LBM can be used for obtaining reliable path travel times. Some comparisons were made and identified that the MAPE difference between the LBM and the PBM estimates are less than 3%, signaling that LBM can be used as a proxy for PBM in case of sparse sample conditions. Some limitations and a future research agenda have also been proposed.