• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.7-16
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• 2004

The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.27-38
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• 2002

VTIS(Value-added Traffic Information System), among the sub-systems of ATIS, is an Advanced Traffic System which innovates efficiency and safety. And this system, having marketability and publicness, is very important. Moreover, This system offers definite traffic information according to the demand of specified users. And it is expected to produce additional spread effects because of high participation rate of private sector. However, the VTIS service media are varied and there are varied optimal Prices and payment methods according to each medium. Because of that, there needs the study on these problems or optimal criteria. But because existing studies were devoted to estimate the optimal route, the study toward the optimal price which was considered part of user and service use demand do not exist. Accordingly, we surveyed under imaginary alternative pricing scenarios and forecasted the use demand of VTIS by using Binary Logit model. Also, for the users who answered that they would use VTIS service in survey, we classified their use's behaviors as four categories and estimated the use ratio to each category by using Ordered Probit model. Last, using sensitivity analysis for results form above, we derived the optimal price that is 2800won in monthly. 145won in payment per call. Then, VTIS service use rate is respectively 65%, 75%.

• International Journal of Railway
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• v.5 no.4
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• pp.139-143
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• 2012

In Korea, almost 700 industrial parks are under operation. Generally, industrial parks consist of national industrial parks and local industrial parks which are managed by a central government and by local governments respectively. The developing countries such as Korea, China and Vietnam etc. have constructed many industrial parks, which result in the change of land use pattern and also affect future trip demands. Therefore, in estimating traffic demands, it is very important to consider the industrial park development. This study aims to improve the methodology in estimating a freight trip generation rate with the data based on a nationwide commodity freight survey. The result showed that it is desirable to apply freight trip generation rate by the industry sector in estimating freight trip generations and using the production area of firm as an indicator. Specially, the reliability of the rates through a survey could be made sure because a sample rate based on firms in industrial parks was over 25% and the response rate was over 67%. The sample rate and response rate are very superior as compared to surveys conducted in many other countries. Because industrial parks have significant effects on forecasting transportation demand in pre-feasibility studies of transport and logistics projects, it is expected that the accuracy of freight trip demands would be improved through the results of this study.

• Journal of Korean Port Research
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• v.15 no.1
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• pp.19-26
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• 2001

The purpose of this study is to improve the strategies for transportation systems of container cargoes in Busan port. Therefore, container cargoes forecasting is done through logistic methods based on past trends. In 2011, container cargoes demand was forecasted 8.791 million TEU(T/S including 12.559 million TEU). In order to improve transportation systems of container cargoes, the conclusions of this study can be summarized as follows ; \circled1 port facilities expansion, \circled2 diversity of container transport modes, \circled3 make up ICD and exclusive container roads, \circled4 the second Seoul-Busan Expressway.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.139-145
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• 2005

`Influence Area` means the area that the traffic flow pattern of which is changed remarkably after the construction of highway facilities. The Influence area would be a significant criteria for demand forecasting and economic analysis. However existing methods for defining influence area such as O/D method, traffic volume variation method and rate of traffic volume variation method have no standard criteria. In this paper, some problems which existing methods have are analyzed and a new method travel time method - is introduced. Influence area can be induced as the area where the vehicles reach from starting traffic zone to ending zone to which 95 percentile vehicles want to travel. In addition, the value of standard criteria for defining influence ayes are induced via this method.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.9-20
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• 2016

Ozone has been a problem in big cities. That is secondary air pollutant produced by nitrogen oxide and VOCs in the atmosphere. In order to solve this, the first to be the analysis of the $NO_x$ and VOCs. The main source of nitrogen oxide is the road mobile. Industrial sources in Seoul are particularly low, and mobile traffics on roads are large, so 45% of total $NO_x$ are estimated that road mobile emissions in Seoul. Thus, it is necessary to clarify the relation with the activity of road mobile source and $NO_x$ concentration. In this study, we analyzed the 4 locations with roadside automatic monitoring systems in their center. The V.K.T. calculating areas are set in circles with 50 meter spacing, 50 meter to 500 meter from their center. We assumed the total V.K.T. in the set radius affect the $NO_x$ concentration in the center. We used the hourly $NO_x$ concentrations data for the 4 observation points in July for the interference of the other sources are minimized. We used the intersection traffic survey data of all direction for construction of the V.K.T. data, the mobile activities on the roads. ArcGIS application was used for calculating the length of roads in the set radius. The V.K.T. data are multiplied by segment traffic volume and length of roads. As a result, the $NO_x$ concentration can be expressed as linear function formula for V.K.T. with high predictive power. Moreover we separated background concentration and concentrations due to road mobile source. These results can be used for forecasting the effect of traffic demand management plan.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1087-1094
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• 2013

This study aims at enhancing the objective estimation of social cost of air quality due to mobile emission. More specifically, it examines the difference between the daily oriented and hourly oriented estimation results of social air quality cost and draws implications from the comparative analysis. The result indicates that the social cost of air quality differs up to approximately 24 times depending on the analysis time period. Moneywise, the difference between daily and hourly assignments amounts to the average of 653.5 billion won whereas only 1% of error occurred in the estimation result based on peak and nonpeak based hourly assignment. This study reaffirms the need for time-based travel demand management for emission reduction, and confirms the feasibility of emission estimation by travel demand forecasting method over the conventional method employed by the CAPSS.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.83-91
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• 2009

This paper aims to predict air passenger and air freight demands in the air routes between South and North Korea. The air demands will be fostered by the visitors of Pyeongyang and Baekdu Mountain, whose forecasts will be used for supplying the air traffic services necessary for the active exchange and cooperation between South and North Korea in the future. The authors use the tool of regression analysis under the assumption of epoch-making progress in demand for aviation in accordance with the exchange and cooperation scenario between South and North Korea. After predicting the total number of travelers through regression analysis, the authors applied the share of air passengers among total travelers in order to predict the number of air passengers. Finally, the number of flights of each airport and route were forecasted by including the air freight, estimated from the number of air passengers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.135-145
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• 2008

As a fundamental input to the travel demand forecasting, OD has been always a concern in obtaining the accurate link traffic volume. Numerous methods were applied thus far without a complete success. Some existing OD estimation techniques generally extract regular samples and expand those sample into population. These methods, however, leaves some to be desired in terms of accuracy. To complement such problems, research on estimating OD using additional information such as link traffic volume as well as sample link use rate have been accomplished. In this paper, a new approach for estimating static origin-destination (OD) using probe vehicle has been proposed. More specifically, this paper tried to search an effective sample rate which varies over time and space. In a sample test network study, the traffic volume error rate of each link was set as objective function in solving the problem. As a key result the MAE (mean absolute error) between expanded OD and actual OD was identified as about 5.28%. The developed methodology could be applied with similar cases. Some limitations and future research agenda have also been discussed.