• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.43-54
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• 2010

In recent years there have been studies on tour based approaches for freight travel demand modelling. The purpose of this paper is to analyze tour type choice behavior of commercial vehicles which are divided into round trips and chained tours. The methods of the study are based on the decision tree and the logit model. The results indicates that the explanation variables for classifying tour types of commercial vehicles are loading factor, average goods quantity, and total goods quantity. The results of the decision tree method are similar to those of logit model. In addition, the explanation variables for tour type classification of small trucks are not different from those for medium trucks', implying that the most important factor on the vehicle tour planning is how to load goods such as shipment size and total quantity.

• International Commerce and Information Review
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• v.13 no.4
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• pp.151-176
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• 2011

Recently, the importance and requirement for Corporate Social Responsibility(CSR) is continuously growing in both korea and foreign countries. This paper tried to analyze on the theoretical trend of CSR and to draw out managemental implications for Korean firms' global CSR strategy by means of comparative case study for the CSR activities of Toyota and Hyundai Motor in China. The results and implications of this study are as follows. First, this study showed that these companies had carried out a systemic legal and ethical responsibility. Second, according to the model of Porter & Kramer and Ibuki Eiko, these companies had recognized the importance of CSR and had recently begun to implement their strategic CSR Third, Toyotas' CSR activities in China are more closely related to auto industry and more strategic in compare with Hyundai Motors' CSR activities in China. Fourth, therefore, the more strategic and long-term planned effective CSR activities of Korean firms in China will be needed in the future.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.35-42
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• 2021

In order to produce electric vehicle demand forecasting information, which is an important element of the plan to expand charging facilities for electric vehicles, a model for predicting electric vehicle demand was proposed using Exponential Smoothing. In order to establish input data for the model, the monthly power demand of cities and counties was applied as independent variables, monthly electric vehicle charging stations, monthly electric vehicle charging stations, and monthly electric vehicle registration data. To verify the accuracy of the electric vehicle power demand prediction model, we compare the results of the statistical methods Exponential Smoothing (ETS) and ARIMA models with error rates of 12% and 21%, confirming that the ETS presented in this paper is 9% more accurate as electric vehicle power demand prediction models. It is expected that it will be used in terms of operation and management from planning to install charging stations for electric vehicles using this model in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.132-144
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• 2023

European and American countries are actively promoting eco-friendly cars to reduce exhaust emissions from internal combustion engines. In Korea, the "4th Basic Plan for Eco-Friendly Vehicles" aims to promote eco-friendly cars by improving charging infrastructure, expanding incentive systems, and targeting the supply of 1.13 million eco-friendly cars by 2025. As rapid growth in the number of electric vehicles sold is expected, estimates are required of this growth and corresponding power demands. In this study, the authors used a growth model to predict future growth in the electric vehicle market and a previously derived electricity generation model to estimate corresponding power demands up to 2036, the target year of the "10th Basic Plan for Power Supply and Demand". The results obtained provide useful basic research data for future electric vehicle infrastructure planning.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.189-195
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• 2006

For the past decades, vehicle emissions has been a major source of air pollution in urban areas Vehicle inspection and maintenance (I/M) test programs were developed for major metropolitan areas to reduce urban air pollution. However. there are a few studies of exploring major factors to influence I/M test failure. This study develops a logit model to identify key factors affecting overall test failure, using the vehicle I/M test data from California in October 2002. The model results indicate that vehicle age, odometer reading, engine size, vehicle make, presences of emissions control equipment, and test types have significant effects on the probability of I/M test failure.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.80-81
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• 2016

자율주행 자동차란 인간에 의한 운전조작이 필요없이 원하는 목적지점까지 안전하게 이동하는 자동차를 말한다. 이러한 자율주행 자동차를 구현하기 위해서는 영상처리를 이용한 여러 기법들이 적용되는데, 본 논문에서는 모형자동차에 영상 처리 기법을 적용하여 자율주행 시스템을 구현하는 과정을 설명한다. 이것은 모형자동차에 무선 카메라를 설치하여 입력받은 영상을 컴퓨터로 보내주고 컴퓨터에서 이를 분석하여 알맞은 신호를 블루투스 통신을 통해서 모형자동차 내의 아두이노로 전송하여 알고리즘에 맞게 동작하는 시스템이다.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.237-252
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• 2013

An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model, autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.84-95
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• 2018

A mathematical model of responsibility-sensitive safety (RSS) has been proposed as a way to determine whether an autonomous driving accident has occurred. Autonomous vehicles related industry and academia have shown great interest in this model. However, this mathematical model lacks a comprehensive review on whether the model can be used to clarify responsibilities of autonomous vehicles in the event of a traffic accident. In this study, we analyzed the issues that need to be solved in order to apply the RSS model. In conclusion, there is a limit in the equation and the social acceptability of the RSS model. To use the RSS model practically, it is necessary to define the response time of the autonomous vehicle and to measure and control the reaction time value according to the appropriate technology level for each autonomous vehicle.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.47-57
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• 2012

The purpose of this study is to propose a supplement to current freight demand model by analyzing factors that influence the generation of empty truck movements in regional and urban realms. To achieve this, we examined the relation between the number of empty truck trips and various generators such as truck attributes, origin type and attributes, destination type and attributes, and commodity type. We structured the ordered logit model using 2011 Korea Transport Database (KTDB) data to analyze the generator characteristic of empty truck movements in regional and urban settings. According to the results, the characteristics of regional and urban empty truck movements differed depending on truck attributes, origin type and attributes, destination type and attributes, and commodity type.

• Environmental and Resource Economics Review
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• v.21 no.2
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• pp.237-269
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• 2012

This study applies a discrete-continuous choice model to a national survey data set of automobile uses to investigate the potential impacts of a bonus-malus system for new cars in Korea. Not only the impacts on the discrete choice of automobile type and class but also those on the continuous decision making of car operation are analyzed. The characteristics of automobiles and individuals that determine car choice and operation are identified. The simulation based on the estimation result shows that an appropriately designed bonus-malus system can induce a reduction in energy consumption and $CO_2$ emission substantially without additional government expenditure.