• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

• 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.18 no.3
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• pp.55-76
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• 2000

We propose a general solution methodology for identifying the optimal aggregation interval sizes as a function of the traffic dynamics and frequency of observations for four cases : i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting. and iv) corridor/route travel time forecasting. We first develop statistical models which define Mean Square Error (MSE) for four different cases and interpret the models from a traffic flow perspective. The emphasis is on i) the tradeoff between the Precision and bias, 2) the difference between estimation and forecasting, and 3) the implication of the correlation between links on the corridor/route travel time estimation and forecasting, We then demonstrate the Proposed models to the real-world travel time data from Houston, Texas which were collected as Part of the Automatic Vehicle Identification (AVI) system of the Houston Transtar system. The best aggregation interval sizes for the link travel time estimation and forecasting were different and the function of the traffic dynamics. For the best aggregation interval sizes for the corridor/route travel time estimation and forecasting, the covariance between links had an important effect.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.5-29
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• 1995

Advanced Traveler Inoformation Systems*ATIS) , as a subsystem of ITS influence the travel choices of dreivers by providing them with historical, real-time and predictive information to supprot travel decisions and consequently improves the speed and quality of travel. For thesuccessul accomplishment of ATIS, the time-dependent variations of traffic in a road network and travel times of vehicles during their journey must be predicted . The purpose of this study is to evaluate the past developments in the dynamic route choice models and to apply the instantaneous dynamic user optimal route choice model. recently formulated with flow propagation constraints by Ran, Boyce and LeBlanc, to the real transportation network of Seocho-Ku in Seoul. As input data for this application, the time-dependent travel rates are estimated and the link travel time function is derived. The modelis validated from three view points : the efficiency of model itself the ability to predict traffic volume and travel time on links, and the optimal traffic control.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.446-457
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• 2018

Forecasting of flood wave travel time is very important in terms of river management and operation. Recently, the hydrological environment of has changed due to the construction of multi-function weir in the river. It is necessary to analyze flood wave travel time, including hydraulic structures in the channel. The flood wave travel time according to the discharge and downstream water level operating conditions was analyzed using HEC-RASver5.0.3 which is capable a two-dimentional analysis. This study showed nonlinear characteristics of flood wave travel times due to increase of discharge and operating conditions. The results of this study will be helpful for the operation of multi-function weir as well as the river operation.

• Geophysics and Geophysical Exploration
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• v.3 no.4
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• pp.119-124
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• 2000

A new fast algorithm for travel time calculation using mono-chromatic one-way wave equation was developed based on the delta function and the logarithms of the single frequency wavefield in the frequency domain. We found an empirical relation between grid spacing and frequency by trial and error method such that we can minimize travel time error. In comparison with other methods, travel time contours obtained by solving eikonal equation and the wave front edge of the snapshot by the finite difference modeling solution agree with our algorithm. Compared to the other two methods, this algorithm computes travel time of directly transmitted wave. We demonstrated our algorithm on migration so that we obtained good section showing good agreement with original model. our results show that this new algorithm is a faster travel time calculation method of the directly transmitted wave for imaging the subsurface and the transmission tomography.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.209-230
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• 2007

This paper analyzed the social cost function of a congestion-prone service system, which is developed from the social cost minimization problem. The analysis focused on the following two issues that have not been explicitly explored in the previous studies: the effect of the heterogeneity of value-of-travel-times among customers on the structure of cost functions; and the structure of the supplier cost function constituting the social cost function. The analysis gave a number of findings that could be summarized as follows. First, the social marginal cost for one unit increase in system output having a certain value-of-travel-time is the sum of the service time cost for that value-of-travel-time and the marginal congestion cost for the average value-of-service-time of all the system outputs. Second, the marginal congestion cost equals the marginal supplier cost of system output under the condition that supplier compensates the customers for the changed service time costs which is incurred by the marginal capacity increase necessary for economically facilitating an additional system output. Third, the compensated marginal cost is the multiple of the marginal capacity cost and the inverse of system utilization ratio, if the service time function is homogeneous of degree zero in its inputs.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.71-79
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• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.395-403
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• 2006

This study suggests the use of a simple method, called the unit concentration response function(UCRF) for predicting travel time and dispersion of pollutants with the minimum information of study area instead of numerical models which are widely used In the Previous studies. However, the numerical models require time-consuming, tedious effort, and many data sets. So we derive the UCRF using some components such as travel time, peak concentration, and passage time of pollutant etc. We use the regression equation for the estimations of components which were developed from the investigations of many river basins in USA. This study used the regression equaiton for the UCRF to the accident of Dichloromethane leak into the Nakdong River occurred on June 30, 1994 and applied the UCRF for the predictions of travel time and dispersion. The predictions were compared with the results by QUAL2E model. The results by the regression equaiton and QUAL2E model had a good agreement between observed and simulated concentrations. Therefore, the regression equation for the UCRF which can simply estimate travel time and concentration of pollutants showed its applicability for the ungaged basin.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.131-138
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• 2012

PURPOSES : Two-lane highways have one lane in each direction, and lane changing and passing maneuvers take place in the opposing lane depending on the availability of passing sight distance. 2001 Korea Highway Capacity Manual (KHCM) is classified into two classes of two-lane highways (Type I, II), and average travel speed and time-delayed rate are used as measures of effectiveness (MOEs). However, since existing two-lane highways have both uninterrupted and interrupted traffic flow-system elements, a variety of free-flow speeds exhibits in two-lane highways. In addition, it is necessary to check if the linear-relationship between volumes and time-delayed rate is appropriate. Then, this study is to reestablish the relationship between average travel speed, time-delayed rate, and flow. METHODS : TWOPAS model was selected to conduct this study, and the free-flow speeds of passenger cars and the percentage of following vehicles observed in two-lane highways were applied to the model as the input. The revised relationships were developed from the computer simulation. RESULTS : In the revised average travel speed vs. flow relationship, the free-flow speed of 90km/h and 70km/h were added. It shows that the relationship between time delayed-rate and flow appeared to be appropriate with the log-function form and that there was no difference in time-delayed rate between the free flow speeds. In addition to revise the relationships, the speed prediction model and the time-delayed rate prediction model were also developed. CONCLUSIONS : The revised relationships between average travel speed, time-delayed rate, and flow would be useful in estimating the Level of Service(LOS) of a two-lane highway.