• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.571-577
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• 2012

Recently, improving public transport service at disabled people has emerged as a social issue in rural areas. By improving expensive and inefficient existing operating system, the rural bus have to change a personalized service. Under these circumstances, government and local governments are promoting the introduction of DRT(Demand response transport). DRT system is intended to promote the user's convenience. But, until now, in-depth research on the operating costs for the introduction of DRT is not well known. This study aims to look at changes in number of vehicle and operating costs before and after introduction of DRT. The results are as follows. Even though introducing DRT, total number of vehicles increases because it does not reduce the existing number of vehicles. And this study estimated to about 5 to 12 percent of the increase in the operating cost comparing before introduction of DRT. Therefore, The introduction of DRT in rural areas is a need to set the exact purpose as promote transportation convenience or cost efficiency.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.65-74
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• 2006

The costs of owning car are accepted as a subscription fee for participating in car-oriented society and only direct out-of-pocket costs of driving are mostly considered, so that the efficient location with better accessibility to service facilities is often under-appreciated. The purpose of this study is to explore the impact of accessibility to public transport and other service facilities on travel demand and transportation cost of household. The residential areas in Hamburg are categorized into 8 types according to level of public transport and other service facilities. The costs of owning and operating car in each residential area are calculated on the base of the household automobile ownership and usage analysed through the actual survey The result of this analysis shows that the transportation cost of household is decreased In proportion to the level of Public transport and other service facilities. This analysis finds the structure of residential area, which economize energy consume and makes household actual transportation cost saying Possible. The result of the analysis can be used as a tool for influencing home locaion choice towards Public transportaion corridors.

• Environmental and Resource Economics Review
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• v.26 no.2
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• pp.173-203
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• 2017

The existence of rebound effect from road extension in Korea has been quantitatively verified using cross-sectional, time series data on four major cities - Seoul, Busan, Daegue and Incheon - between 2000 and 2013. The linear mixed effects model was constructed from six variables: total vehicle miles traveled (VMT), road extension, public transport users, gross regional domestic product (GRDP), regional population and fuel consumption. The main results can be summarized as VMT is positively correlated to road extension while negatively with public transport users. It indicates that the road extension-centered "supply-side" transportation policy induces "additional travel" and create "generated traffic" by enhancing driving efficiencies directly, or degrading other transport modes indirectly. Hence, the ultimate goal of road congestion reduction requires public transport-centered "demand management" rather than current supply-side policies.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.81-89
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• 2011

Trip distribution is the second step of the conventional travel demand estimation process, which connects trips between origin and destination, while transport mode choice is the third step of the process, which chooses transport mode among several modes serving for each origin-destination pair. Although these two steps have closely connected, they have been estimated independently each other in the estimation procedure. This paper presents an integrated model combining trip distribution and transport mode choice, and also presents its solution algorithm. The model integrates gravity model adopted for the trip distribution process with logit model employed for the mode choice process. The model would be expected to cope with the inconsistency issue existing in the conventional travel demand estimation procedure. This paper also presents an equilibrium condition, sensitivity of the model, and compares them with those of existing models.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.28-37
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• 2020

This study developed a deep learning model that predicts rental demand for public bicycles. For this, public bicycle rental data, weather data, and subway usage data were collected. After building an exponential smoothing model, ARIMA model and LSTM-based deep learning model, forecasting errors were compared and evaluated using MSE and MAE evaluation indicators. Based on the analysis results, MSE 348.74 and MAE 14.15 were calculated using the exponential smoothing model. The ARIMA model produced MSE 170.10 and MAE 9.30 values. In addition, MSE 120.22 and MAE 6.76 values were calculated using the deep learning model. Compared to the value of the exponential smoothing model, the MSE of the ARIMA model decreased by 51% and the MAE by 34%. In addition, the MSE of the deep learning model decreased by 66% and the MAE by 52%, which was found to have the least error in the deep learning model. These results show that the prediction error in public bicycle rental demand forecasting can be greatly reduced by applying the deep learning model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.81-91
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• 2012

The world has been replacing fast fossil fuels vehicles with electric vehicles(EVs) to cope with climate change. The government set a goal which EVs will be substitute at least 10% of the domestic small vehicles with EVs until 2020, and will try to build electric charging infrastructures in apartments with the revision the law of 'the housing construction standards'. In apartments the EVs charging infrastructure and parking space is, essential to accomplish the goal. But the studies on EVs demand are few. In this study, we predicted that the demand for EVs using time-series analysis of statistical data, survey results for apartments residents in the metropolitan area. As a result, the ratio of the EVs appeared to be 6~21% for the total vehicles in a rental apartments for the years 2020, 21~39% in apartments for sales. For the EVs, the maximum power required for 1,000 households in rental apartment is predicted to be about 4200 kwh on a daily basis, while the maximum power in the apartment for sales is predicted to be 7800kwh.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.1-11
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• 2013

This research proposed integrated expressway traffic management strategy using ramp metering and toll mainline metering. This research suggested a traffic signal optimization model for integrated operation of ramp and mainline metering based on Demand-Capacity Model that is used to optimize allowable input volume for ramp metering in FREQ model. The objective function of this model is sectional throughput volume maximization, and this model can calculate optimal signal timings for mainline metering and ramp metering. This study conducted an effectiveness analysis of integrated metering strategy using PARAMICS and its API. It targeted Seoul's Outer Ring Expressway between Gimpo and Siheung toll gate. As a simulation result, integrated operation of mainline and ramp metering provided more smooth traffic flow, and throughput volume of mainline increased to 14% in congested section. In addition, a queue of 400 meter was formed at metering point of toll gate. This research checked that integrated traffic management strategy facilitates more efficient traffic operation of mainline and ramp from diffused traffic congestion.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.138-143
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• 2013

Recently, the demand for rail freight has gradually decreased. In particular, the demand in Korea for open freight cars, which classification includes gondola cars, hopper cars and gravel cars has been significantly reduced. The role of gondola cars in the rail transportation market shrank to 14.5% in 2010 from 23.3% in 2001. The transportation demand of gondola cars in the long term is expected to be reduced further. Because some gondola cars have been converted to container cars and various containers are being developed to transport bulk cargo by container cars. However, gondola cars still play an important role in rail freight transport. Therefore, the management planning of gondola cars is needed in order to prepare for the long-term declining demand. In this study, we propose a future direction for the management planning of gondola cars through the effectiveness analysis of gondola cars operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.57-69
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• 2022

Even though demand to charge EV(electric vehicles) is increasing, there are some problems to construct EV charging stations and problems from deficient them. Typical problem of EV charging stations is discordance for EV charging station location with its demand. This study investigates methods to determine the optimized location for fast EV charging stations considering charging demand in Seoul. Firstly, variables influencing on determination of determine the optimized location for fast EV charging stations were decided, and then evaluation of weights of the variables and data collection were conducted. Using the weights, location potential scores for each area-cell were calculated and optimized locations for fast EV charging stations were resulted.