• Korean Journal of Hazardous Materials
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• v.6 no.2
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• pp.68-76
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• 2018

This study aims to provide a methodological framework to estimate the travel demand of hazardous materials transporting vehicles by link and analyze daily traffic patterns on an expressway to develop safety roadway management strategies. Traffic volume of hazardous material vehicles is counted through the on-site investigation at twenty-five tollgates on the expressway, and their demands by a link are predicted through origin-destination flows estimation. The result shows that the number of the domestic hazardous materials vehicles is approximately 51,207 vehicles per day and it indicates that hazardous materials transport vehicles account for 1.5% of total daily traffic on the internal expressway and 6.2% of total cargo traffic volumes. This study roughly estimated how many hazardous materials vehicles pass through the expressway segment. Thus it is expected to be utilized for establishing a systematic highway management strategy in the future by calculating the traffic volume of the hazardous material vehicles traveling on the interstate expressway.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.107-122
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• 2016

This study aims to develop a framework to estimate mobile source emissions with the macroscopic travel demand model including enhanced estimates of intra-zonal travel emissions using Space Syntax analysis. It is acknowledged that "the land-use and transportation interaction model explains the influence of urban structure on accessibility and mobility pattern". Based upon this theory, the estimation model of intra-zonal travel emissions is presented with the models of total travel distance, total travel demand, and average travel speed of intra-zonal trips. Thess statistical models include several spatial indices derived from the Space Syntax analysis. It explains that urban spatial structure is a critical factor for intra-zonal travel emissions, which is lower in compact zone with smaller portion of land area, lower sprawl indicator, and more grid-type of road network. Also the suggested framework is applied in the evaluation of the effectiveness of bicycle lane project in Suwon, Korea. The estimated emissions including intra-zonal travel is as double as the results only with inter-zonal demands, which shows better performance of the suggested framework for more realistic outcomes. This framework is applicable to the estimation of mobile source emissions in nation-wide and the assessment of transportation-environment policies in regional level.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.145-158
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• 2015

A network connectivity has been regarded as a key element to strengthen a business competitive power in the aviation industry, so many airport authorities try to attract the new airlines and scheme out new air routes. With this trend, a study for an induced travel demand estimation methodology is needed. This study introduces a demand estimation method, especially for a new air route to a promising destination. With the results of previous studies, the derived demand is classified into four types - Local, Beyond, Behind and Bridge. The explanatory variables are established for each type of demand and the main independent variables are composed of distance, ratio of detour, and relative capacity compared with other airports. The equations using such variables and statistically significant coefficients are suggested as the model to make an estimation of derived demand for a new route. Therefore this study will be expected to take an initial step for all related parties to be involved more deeply into developing new air routes to enhance network connectivity.

• 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.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.85-93
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• 2011

Many policies, such as transit-oriented development, encouraged use of bicycle and pedestrian, reduction of green house gas (GHG) and etc., have been deployed to support transport sustainability. Although various studies regarding GHG were presented, no one has yet adequately explained the behavior of travelers. This paper proposes a GHG emission model by highlighting its sensitivity, elasticity with regard to such travel cost as travel time, travel fare, and GHG pricing, introduced to reduce the amount of GHG in transportation system. For better estimation of GHG, the proposed model adopts (1) a production-constrained gravity model and (2) the travel distance from the origin and the destination (OD). The gravity model has a merit that it considers travel pattern between OD pairs. The model was tested with an example, and the promising results confirmed its validation and applications.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.77-88
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• 2001

Until now, though most of the studies related to demand estimation method using traffic counts use methods based on singleclass, travel demands or flows are made by mixing various vehicles in real networks. In general, existing demand estimation methods based on traffic counts estimate O/D by converting a multiclass O/D matrix and traffic counts into a singleclass O/D matrix and traffic counts through PCE conversion, and analyze a O/D matrix by dividing into a multiclass O/D matrix and traffic counts after multiplying an estimated O/D matrix by the fixed ratio of a singleclass O/D matrix and traffic counts before PCE conversion. However, the merits of a demand estimation method based on multiclass calculate each route choice ratio about multiclass O/D, and maximize the estimation capability of multiclass by calculating each gradient, the reduction direction of objective function. Therefore, this study aims to establish a demand estimation method which considers congestion between vehicle and vehicle by using multiclass instead of singleclass.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.114-128
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• 2013

Greenhouse gas emissions have been an important issue in different countries because of their effects on global warming. The government has to organize greenhouse gas reduction measures suitable to regional characteristics by establishing annual implementation plans and comprehensive policies based on the UNFCCC. The transportation sector is one of the major contributors of air pollution; hence increasing need to estimate current and future traffic emissions precisely. Under these circumstances, a number of emission models have been developed recently. However, current methods of estimation cannot carry out effective analyses because it does not reflect vehicle movement characteristics. This study aims to present a new method for calculating road traffic emissions in Goyang city. A travel demand model is utilized to carry out GHG emission estimates according the traffic data (fleet composition, vehicle kilometers travelled, traffic intensity, road type, emission factors and speed). This study evaluates two approaches to estimate the road traffic emissions in Goyang City: Pollution-Emis and the Handbook of Emission Factors for Road Transport (HBEFA v.3.1) which is representative of the "average speed" and the "traffic situation" model types. The evaluation of results shows that the proposed emission estimation method may be a good practice if vigilant implementation of model inputs is observed.

• International Journal of Railway
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• v.7 no.1
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• pp.24-33
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• 2014

The Korean high-speed rail (HSR) began its commercial service in 2004. This service has been created significant changes in the system of intercity passenger travels of Korea. However, the actual ridership was approximately half of the estimated one in the planning stage. In this background, this paper presents the difference between the stated preference (SP) before the HSR service and the revealed preference (RP) after it using the intercity travel mode choice models. Several meaningful differences are found in terms of the factors affecting the travel mode choice, the estimation results of model, the monetary values of time, and elasticities. While the access/egress travel time of high-speed rail is less important than in-vehicle travel time in the SP sample, they have same weight in the RP sample. Also the RP models show that the probability of choosing HSR can be decreased by the increase of the number of vehicles in household contrary to the results from the SP models. The monetary values of travel time are relatively high and the direct and cross elasticities in response to changes in level-of-service of HSR are relatively low in the RP sample. This Korean case is expected to offer referable material for preparing high-speed rail services in other countries by showing the difference between the SP and RP before/after the actual service, identifying the importance of access/egress travel time and lower direct elasticities of HSR demand.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.97-116
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• 1999

The growing demand for the real time traffic information is bringing about the category and number of traffic collection mechanism in the era of ITS. There are, however, two problems in making data into information using various traffic data. First, the information making process of making data into the representative information, for each traffic collection mechanism, for the specified analysis periods is required. Second, the integration process of fusing each representative information into "the information" for each link out of each source is also required. That is, both data reduction and/or data to information process and information fusion are required. This article is focusing on the development of information fusing algorithm based on voting technique, fuzzy regression, and, Bayesian pooling technique for estimating the dynamic link travel time of networks. The proposed algorithm has been validated using the field experiment data out of GPS probes and detectors over the roadways and the estimated link travel time from the algorithm is proved to be more useful than the mere arithmetic mean from each traffic source.

• 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.