• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.43-54
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• 2010

In order to improve the existing evaluation system of bus services and gain more reasonable analysis outputs, the authors evaluate the efficiency of 113 arterial bus routes in Seoul in 2009 using a modified BCC model considering not only desirable outputs but also undesirable outputs. Each Decision Making Unit (DMU) is assumed to use inputs such as possession costs, operating costs, the ratios of median bus stops overlapped route lengths to produce estimates of desirable outputs (the number of passengers and service satisfaction score) and undesirable outputs (CO2 emissions). According to the analysis, the modified BCC model considering both desirable outputs and undesirable outputs shows more appropriate results. DMUs would be more efficient on average to reduce nearly 10% of the 3 inputs (possession costs, operating costs, and overlapped route lengths) and increase by about 160% the ratios of median bus stops. Also, a Tobit regression analysis is conducted to identify the most effective variables for maximum efficiency and discover that the variable of possession costs and the ratios of median bus stops are statistically significant.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.43-54
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• 2021

Since COVID-19 (Severe acute respiratory syndrome coronavirus type 2, SARS-Cov-2) was first discovered at the end of 2019, it has spread rapidly around the world. This study introduces an agent-based simulation model representing COVID-19 spread in South Korea to investigate the effect of detect level (contact tracing) on the virus spread. To develop the model, related data are aggregated and probability distributions are inferred based on the data. The entire process of infection, quarantine, recovery, and death is schematically described and the interaction of people is modeled based on the traffic data. A composite logistic functions are utilized to represent the compliance of people to the government move control such as social distancing. To demonstrate to effect of detect level on the virus spread, detect level is changed from 0% to 100%. The results indicate active contact tracing inhibits the virus spread and the inhibitory effect increases geometrically as the detect level increases.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.193-204
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• 2022

Smart card data is representative mobility data and can be used for policy development by analyzing public transportation usage behavior. This paper deals with the problem of classifying metro stations using metro usage patterns as one of these studies. Since the previous papers dealing with clustering of metro stations only considered traffic among usage behaviors, this paper proposes clustering considering traffic time as one of the complementary methods. Passengers at each station were classified into passengers arriving at work time, arriving at quitting time, leaving at work time, and leaving at quitting time, and then the estimated shape parameter was defined as the characteristic value of the station by modeling each transit time to Weibull distribution. And the characteristic vectors were clustered using the K-means clustering technique. As a result of the experiment, it was observed that station clustering considering pass time is not only similar to the clustering results of previous studies, but also enables more granular clustering.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.147-155
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• 2005

The purpose of this paper is to develop a method for estimation of reliable path-travel time using data obtained from the toll collection system on freeways. The toll collection system records departure and arrival time stamps as well as the identification numbers of arrival and destination tollgates for all the individual vehicles traveling between tollgates on freeways. Two major issues reduce accuracy when estimating path-travel time between an origin and destination tollgate using transaction data collected by the toll collection system. First, travel time calculated by subtracting departure time from arrival time does not explain path-travel time from origin tollgate to destination tollgate when a variety of available paths exist between tollgates. Second, travel time may include extra time spent in service and/or rest areas. Moreover. ramp driving time is included because tollgates are installed before on-ramps and after off-ramps. This paper describes an algorithm that searches for arrival time when departure time is given between tollgates by a Progressive Iterative Forward and Backward (PIFAB) search method. The algorithm eventually produces actual path-travel times that exclude any time spent in service and/or rest areas as well as ramp driving time based on a link-based procedure.

• Land and Housing Review
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• v.3 no.3
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• pp.241-248
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• 2012

Although infrastructure cost comprises the great proportion of residential development cost, all of it tends to be borne by land developers which develop large area. This brings about free-riding by adjacent small development or built-up area, followed by the equity problem in terms of infrastructure development cost sharing and the privatization of development gain. This study aims to establish the method to analyze free-riding on the transportation infrastructure(roads) and investigate empirically how much the free-riding occurs. It sets several development scenarios to calculate the part generated by Bucheon Sangdong district, the case area of this study, of all the traffic flow on the roads. The Network analysis is used to estimate the proportion, by development scenarios, of traffic flow, travel time, and travel cost. As a result, the developer of Bucheon Sangdong district is responsible for 83% of the construction cost of selected roads. The methodology and empirical result of this study would contribute to determine who are liable for the infrastructure facilitation and to estimate how much of the cost the obligators have to share.

• Particle and aerosol research
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• v.14 no.4
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• pp.97-105
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• 2018

Recently, people's interest in particulate matter (PM) has been increasing, due to its hazardous health effects. The purpose of this study was to investigate the concentrations and as well as the inhaled weight of PM, correlated with person's heart rate in subway, bus, vehicle and bicycle in the major public transportation (Sadang - Jamsil and Nowon - Dongdaemun) in Seoul. The concentration of $PM_{10}$ and $PM_{2.5}$ were measured from each of transportation means and calculated the average concentrations which were 87.2 and $57.8{\mu}g/m^3$ for subway, 62.8 and $42.5{\mu}g/m^3$ for vehicle, 61.5 and $36.8{\mu}g/m^3$ for bus and 53.0 and $29.4{\mu}g/m^3$ for bicycle in $PM_{10}$ and $PM_{2.5}$ respectively. Inhalation dose for $PM_{10}$ and $PM_{2.5}$ were estimated at 248.1 and $139.4{\mu}g$ for bicycle, 56.7 and $39.3{\mu}g$ for vehicle, 49.4 and $29.9{\mu}g$ for bus and 44.3 and $29.1{\mu}g$ for subway, respectively. Even though subway had the highest concentration, the highest inhalation dose was the bicycle. It was due to the long travel time-exposure and breathing rate which leads to maximum of $PM_{10}$ 5.6 and $PM_{2.5}$ with 4.8 times inhalation dose comparing with other modes of transportation. With regards to future studies, the amount of inhalation in each transportation means should be considered in risk assessments of PM.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.3
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• pp.273-278
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• 1995

This study is to estimate the ventilation volume by the traffic that originated from driving automobiles for two tunnels (Kugi tunnel and Kumhwa tunnel) that adopted natural ventilation system among tunnels of Seoul, and on the basis of which, we estimated the ventilation velume at various conditions. With the result of the estimation, we will present the basic method that can be operated with the optimum condition for the ventilation system. Estimating the predicted ventilation volume in the tennel by the pollutant concentration, we used traffic volume and CO emission data by the automobile speed and CO concentration in the tunnel. And, when we estimated the traffic ventilation volume by natural and traffic ventilation force, we used traffic volume, automobile speed, tunnel area, automobile area data and so on. As the result of simple regression between predicted ventilation volume and traffic ventilation volume, we attained the regression coefficient 0.88, and achieved the relation form that predicted ventilation volume equal 0.12x traffic ventilation volume-92, 000. Using this equation, we estimated the ventilation volume to satisfy the enviromnental standards of several space, and calculated the required volume for mechanical ventilation. Incase of Kumhwa Tunnel, there is a need of mechanical ventilation all day long to satisfy air quality standard 9 ppm for 8 hours average and 10 ppm for the indoor air quality standard of public facilities.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.559-564
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• 2006

The purpose of this study is to minimize negative effect of VMS travel time information service by sensitivity analysis, which forecasts the change in link traffic volume. As a result, strategies for providing travel information that can change driving patterns for minimizing travel time were found. The framework for analysis is recently expanded with the application of game theory. According to the experiment, the algorithm generated for travel time information service reduces total travel time and yields travel patterns that is very close to the system optimization. Also, this study found that the route the travel time service information is provided about could play the important role.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.51-61
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• 2023

Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.