• International Journal of Highway Engineering
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• v.17 no.2
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• pp.107-122
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• 2015

PURPOSES : The use of virtual driving tests to determine actual road driving behavior is increasing. However, the results indicate a gap between real and virtual driving under same road conditions road based on ergonomic factors, such as anxiety and speed. In the future, the use of virtual driving tests is expected to increase. For this reason, the purpose of this study is to analyze the gap between real and virtual driving on same road conditions and to use a calibration formula to allow for higher reliability of virtual driving tests. METHODS : An intelligent driving recorder was used to capture real driving. A driving simulator was used to record virtual driving. Additionally, a virtual driving map was made with the UC-Win/Road software. We gathered data including geometric structure information, driving information, driver information, and road operation information for real driving and virtual driving on the same road conditions. In this study we investigated a range of gaps, driving speeds, and lateral positions, and introduced a calibration formula to the virtual record to achieve the same record as the real driving situation by applying the effects of the main causes of discrepancy between the two (driving speed and lateral position) using a linear regression model. RESULTS: In the virtual driving test, driving speed and lateral position were determined to be higher and bigger than in the real Driving test, respectively. Additionally, the virtual driving test reduces the concentration, anxiety, and reality when compared to the real driving test. The formula includes four variables to produce the calibration: tangent driving speed, curve driving speed, tangent lateral position, and curve lateral position. However, the tangent lateral position was excluded because it was not statistically significant. CONCLUSIONS: The results of analyzing the formula from MPB (mean prediction bias), MAD (mean absolute deviation) is after applying the formula to the virtual driving test, similar to the real driving test so that the formula works. Because this study was conducted on a national, two-way road, the road speed limit was 80 km/h, and the lane width was 3.0-3.5 m. It works in the same condition road restrictively.

• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1120-1130
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• 2020

The CREOLE experiment performed In the EOLE critical facility located In the Nuclear Center of CADARACHE - CEA have allowed us to get interesting and complete experimental information on the temperature effects in the light water reactor lattices. To analyze these experiments with accuracy an elaborate calculation scheme using the Monte Carlo method implemented in the MCNP6.1 code and the ENDF/B-VII.1 cross section library has been developed. We have used the ENDF/B-VII.1 data provided with the MCNP6.1.1 version in ACE format and the Makxsf utility to handle the data in the specific temperatures not available in the MCNP6.1.1 original library. The main purpose of this analysis is the qualification of the ENDF/B-VII.1 nuclear data for the prediction of the Reactivity Temperature Coefficient while ensuring the ability of the MCNP6.1 system to model such a complex experiment as CREOLE. We have analyzed the case of UO₂ lattice with 1166 ppm of boron in ordinary water moderator in specified temperatures. A detailed comparison of the calculated effective multiplication factors with the reference ones [1] in room temperature presented in this work shows a good agreement demonstrating the validation of our 3D calculation model. The discrepancies between calculations and the differential measurements of the Reactivity Temperature Coefficient for the analyzed configuration are relatively small: the maximum discrepancy doesn't exceed 1,1 pcm/℃. In addition to the analysis of direct differential measurements of the reactivity temperature coefficient performed in the poisoned UO₂ lattice configuration, we have also analyzed integral measurements in UO₂ clean lattice configuration using equivalency of the integral temperature reactivity worth with the driver core fuel reactivity worth and soluble boron reactivity worth. In this case both of the ENDF/B-VII.1 and JENDL.4 libraries were used in our analysis and the obtained results are very similar.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.41-52
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• 1999

Recently, much literature has surveyed the economic effects of transportation investment, focusing on the relationship between transportation infrastructure investment and economic development. Although the conventional views assume that transportation investment stimulates economic growth, the results of recent studies are not conclusive and in some cases reject the conventional views. The contradictory results are linked with double counting Problem and Keynesian/Neo-classical economics theory. This article investigates the economic effects of road transportation with regard to freight transport using Stated Preference technique. This study examines, in particular, the value of time saving for freight which has been rarely studied in this area. In the first part, the value of time saving, excluding the value for driver and operating cost, is theoretically investigated through the model of continuous review system and periodic review system. At last, the empirical study using the Seated Preference technique shows the value of time saving for freight and the value of reliability, compared with other studies and the value of those in COBA. The result makes us conclude that road investment produces the secondary effects as well as the direct benefit such as time saving for passengers, operating cost saving. and accident cost reduction. The secondary effect includes the contribution to economic development.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.29-48
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• 2011

Recently not only industry but also academy have shown an intense interest in social networking service. However, reckless imitation will not guarantee the successful eco-system of social networking service without rich understanding of growth driver and business model. Hence, this study aims at analyzing open platform strategy and business model conducted by a representative social networking service provider in order to provide platform operator, network operator, and portal provider with meaningful implications. Advertisers may pay great attention to social networking service because it has strong ability to provide users with spontaneous motivation to manage and update their profile, and these valuable information can be utilized for providing personalized advertisement on social networking service. As a result, one side of consumers in two side market, advertisers, tend to pay more expenditure to place advertisements. In addition, the open platform adopted by social networking service providers causes pro-sumers to participate in the eco-system, and thereby the explosive quantitative growth is realized. The fact of that this open social networking service can invade other web service area via an unified platform indicates that it may expand its service scope into a wide variety of web service areas. Hence, domestic portal services providers and network providers should consider social networking service not as one of new web services but as an disruptive service platform. Corresponding to the emergence of social networking service, especially if their business area is related to display advertising market, they should seek a way to provide social networking service access users's newly updated information and develop innovative media technologies to enter context awareness ads market.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.73-82
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• 2017

As of December 2016, the number of registered automobiles in Korea exceeds 21million. As a result, greenhouse gas emission by transportation sector are increasing every year. It was concluded that the development of the driving strategy considering the driving behavior and the road conditions, which are known to affect the fuel efficiency and the greenhouse gas emissions, could be the most effective fuel economy improvement. Therefore, this study aims to develop a fuel efficient driving strategy in a complex linear section with uphill and curved sections. The road topography was designed according to 'Rules about the Road Structure & Facilities Standards'. Various scenarios were selected. After generating the speed profile, it was applied to the Comprehensive Modal Emission Model and fuel consumption was calculated. The scenarios with the lowest fuel consumption were selected. After that, the fuel consumption of the manual driver's driving record and the selected optimal driving strategy were compared and analyzed for verification. As a result of the analysis, the developed optimal driving strategy reduces fuel consumption by 21.2% on average compared to driving by manual drivers.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.109-121
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• 2006

The road should be designed in the consistent alignment which the driver can drive safely. Also, proper highway environments in order to maintain optimal operational speeds on highway sections should be provided In design stage, for highway environments, it is essential for an operational speed estimation model to different highway environments. If a method which could evaluate the status of the road safety is developed through this operational speed estimation model, it is possible to provide safe and more comfortable highways to road users. In the study factors to effect on operational speeds are classified into three groups horizontal & vertical alignments and traffic operation characteristic factors. Factors are chosen to effect on operational speeds by using collation analysis as classifications of tangent sections, horizontal curve sections and vertical curve sections. In order to develop operational speed estimation models in express highways, multi-regression analysis has been used in this study using the selected factors. This study has meaning that the developed estimation models for operational speeds and evaluation of degree of safety to horizontal and vortical alignments simultaneous. In order to represent whole area of the country with the developed models, the models should be re-analyzed with vast data related with road alignment factors in the near future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.63-72
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• 2014

With the rapid development in the economy and other fields as well, the standard of living in South Korea has been improved, and consequently, the demand of automobiles has quickly increased. It leads to various traffic issues such as traffic congestion, traffic accident, and parking problem. In particular, this illegal parking caused by the increase in the number of automobiles has been considered one of the main reasons to bring about traffic congestion as intensifying any dispute between neighbors in relation to a parking space, which has been also coming to the fore as a social issue. Therefore, this study looked into Daejeon Metropolitan City, the city that is understood to have the highest automobile sharing rate in South Korea but with relatively few cases of illegal parking crackdowns. In order to investigate the theoretical problems of the illegal parking, this study conducted a decision-making tree model-based Exhaustive CHAID analysis to figure out not only what makes drivers park illegally when they try to park vehicles but also those factors that would tempt the drivers into the illegal parking. The study, then, comes up with solutions to the problem. According to the analysis, in terms of the influential factors that encourage the drivers to park at some illegal areas, it was learned that these factors, the distance, a driver's experience of getting caught, the occupation and the use time in order, have an effect on the drivers' deciding to park illegally. After working on the prediction model, four nodes were finally extracted. Given the analysis result, as a solution to the illegal parking, it is necessary to establish public parking lots additionally and first secure the parking space for the vehicles used for living and working, and to activate the campaign for enhancing illegal parking crackdown and encouraging civic consciousness.

• Korean Journal of Culture and Social Issue
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• v.22 no.1
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• pp.19-39
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• 2016

Though research has shown that public transportation drivers experience greater burnout than other drivers, the sources of their burnout and possible mediators remain largely unknown. In response, in this study we investigate the relationships among sensation seeking, Type A driving behavior, and meaning of work to elucidate the burnout experienced by bus drivers in Gyeonggi-do, South Korea. To collect data regarding these relationships, 188 bus drivers answered a questionnaire involving the sensation seeking scale, burnout scale, and meaning of work scale. Results showed that Type A driving behavior mediated the relationship between sensation seeking and burnout, while meaning of work moderated the mediated model. These findings demonstrate that sensation-seeking bus drivers tend to experience greater burnout given their tendency to exhibit Type A driving behavior, and this relationship depends on perceived meaning of work. This study therefore contributes meaningful information and outlines significant implications in understanding drivers' burnout.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Smart Media Journal
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• v.12 no.11
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• pp.57-66
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• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.