• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.28-41
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• 2022

A road system with CV(Connected Vehicle)s, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides various road information to drivers using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed or change lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behaviors from a traffic safety point of view. Thus, empirically evaluating how a given in-vehicle warning information affects driving behaviors, and monitoring of the correlation between them are essential tasks for traffic operators. To quantitatively evaluate the effect of in-vehicle warning information, this study develops a method to calculate compliance rate of drivers where two groups of speed profile before and after road information is provided are compared. In addition, conventional indexes (e.g., jerk and acceleration noise) to measure comfort of passengers are examined. Empirical tests are conducted by using PVD (Probe Vehicle Data) and DTG (Digital Tacho Graph) data to verify the individual effects of warning information based on C-ITS constructed in Seoul metropolitan area in South Korea. The results in this study shows that drivers tend to decelerate their speed as a response to the in-vehicle warning information. Meanwhile, the in-vehicle warning information helps drivers to improve the safety and comport of passengers.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.189-200
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• 2023

As urbanization and industrialization increase development in downtown areas, damage due to ground settlement continues to occur. Building collapse in urban has a high risk of leading to large-scale damage to life and property. However, there has rarely been studied on measurement data analysis methods when uneven loads are applied to the excavated ground and no prior knowledge of the ground. Accordingly, it was attempted to analyze the relative settlement behavior and correlation by processing the time-series surface settlement of construction sites in the urban. In this paper, the average index of difference in settlement and average of relative difference in settlement are defined and calculated, then plotted in the coordinate system to analyze the relative settlement behavior over time. In addition, since there was no prior knowledge of the ground, a standard to classify the clusters was needed, and the observation points were classified into using k-means clustering and Dunn Index. As a result of the analysis, it was confirmed that all the clusters moved to the stable region as the settlement amount converges. The clusters were segmented. Based on the analysis results, it was possible to distinguish between the independent displacement area and same behavior area by analyzing the correlation between measurement points. If possible to analyze the relative settlement behavior between the stations and classify the behavior areas, it can be helpful in settlement and stability management, such as uplift of the surrounding area, prediction of ground failure area, and prevention of activity failure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.45-54
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• 2023

The settlement prediction during the design phase is primarily conducted using theoretical methods. However, measurement-based settlement prediction methods that predict future settlements based on measured settlement data over time are primarily used during construction due to accuracy issues. Among these methods, the hyperbolic method is commonly used. However, the existing hyperbolic method has accuracy issues and statistical limitations. Therefore, a weighted nonlinear regression hyperbolic method has been proposed. In this study, two weighting methods were applied to the weighted nonlinear regression hyperbolic method to compare and analyze the accuracy of settlement prediction. Measured settlement plate data from two sites located in Busan New Port were used. The settlement of the remaining sections was predicted by setting the regression analysis section to 30%, 50%, and 70% of the total data. Thus, regardless of the weight assignment method, the settlement prediction based on the hyperbolic method demonstrated a remarkable increase in accuracy as the regression analysis section increased. The weighted nonlinear regression hyperbolic method predicted settlement more accurately than the existing linear regression hyperbolic method. In particular, despite a smaller regression analysis section, the weighted nonlinear regression hyperbolic method showed higher settlement prediction performance than the existing linear regression hyperbolic method. Thus, it was confirmed that the weighted nonlinear regression hyperbolic method could predict settlement much faster and more accurately.

• Journal of the Korean Geotechnical Society
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• v.25 no.1
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• pp.5-19
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• 2009

Most of earthquake-induced geotechnical hazards have been caused by the site effects relating to the amplification of ground motion, which is strongly influenced by the local geologic conditions such as soil thickness or bedrock depth and soil stiffness. In this study, an integrated GIS-based information system for geotechnical data, called geotechnical information system (GTIS), was constructed to establish a regional counterplan against earthquake-induced hazards at an urban area of Daejeon, which is represented as a hub of research and development in Korea. To build the GTIS for the area concerned, pre-existing geotechnical data collections were performed across the extended area including the study area and site visits were additionally carried out to acquire surface geo-knowledge data. For practical application of the GTIS used to estimate the site effects at the area concerned, seismic zoning map of the site period was created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation for site classification according to the spatial distribution of the site period was also performed to determine the site amplification coefficients for seismic design and seismic performance evaluation at any site in the study area. Based on this case study on seismic zonations in Daejeon, it was verified that the GIS-based GTIS was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation.

• Journal of the Korean Geotechnical Society
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• v.25 no.2
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• pp.55-66
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• 2009

At the mudstone slope located on the roadside of the Seokri area in Donghae-myeon, Pohang, Gyeongsangbuk-do, this study was performed to analyze the effects of rainfall on the stability of slope through seepage analysis according to the precipitation type of the mudstone slope, referring to the actual case of slope failure. For this, precise geological survey, geophysical exploration and drilling survey for the slope where the failure occurred were performed and followed by analysis of detailed soil layer. For the section where failure surface located, the durability reduction of rocks was measured through slaking/swelling tests and the permeability was measured through in-situ permeability tests for each soil layer. In addition, the change of strength parameter and process of instability were analyzed by back analysis, using Talren 97 and Slope/W programs, in the slope. By applying different precipitation conditions to the geographical conditions of the slope that had actual failure records, the slope stability was analyzed by seepage analysis according to duration of rainfall and rise of groundwater level resulting from the flow of rainfall caused by development of geological structures and the slope surface condition.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.118-124
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• 2023

Objectives : Depressive disorder and anxiety disorder frequently co-occur, even at sub-threshold level. This study aims to identify network structure of co-morbid depression and anxiety at symptom level in nonclinical population and to reveal the central symptoms and bridge symptoms of the co-morbidity. Methods : This study was based on 2022 Asan Youth Mental Health Screening. Patient health questionnaire (PHQ-9) and Generalized anxiety disorder scale (GAD-7) were used to assess depressive and anxiety symptoms of 810 young adult participants from community sample. Network structure of co-morbid depressive and anxiety symptoms was estimated by Isingfit model. Results : Depressed mood, Restlessness and Nervousness were the most central symptoms in the network. Bridge symptoms between anxiety and depression were Restlessness and Irritability. Conclusions : This study revealed key central symptoms and bridge symptoms of co-morbid depression and anxiety in nonclinical population and provided potential insight for treatment targets to reduce co-morbidity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.224-239
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• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.181-196
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• 2024

This study examines the impact of university graduate Startup rates on economic growth in the regions where universities are located, using panel data from 35 universities in 17 regions in Korea and 21 universities in 13 cities in China over a six-year period from 2016 to 2021. In Korea, a total of 35 universities were selected as part of the Ministry of Education's "University-initiated Startup" policy, including Startup-oriented universities, leading universities in Startup education innovation, Startup education bases, and excellent universities in Startup education, while in China, 21 universities were selected as part of the pilot bases established as part of the "Mass Entrepreneurship, Mass Innovation" policy. To analyze the economic impact of the universities on the regions where they are located, we aimed to conduct an empirical analysis of the economic impact using economic indicators of the economic growth rate of the regions where they are located. The results of the empirical analysis show that the Startup rate of university graduates in Korea and China both have a positive impact on the regional economic growth rate, but the Startup rate of local university graduates in Korea has a greater impact on the regional economy than in China. Based on the findings that the number of entrepreneurs produced by universities has a positive impact on the economic growth of their regions, this study draws implications for the role of universities and regions in revitalizing local economies and the establishment of systems to resolve the imbalance between metropolitan and non-metropolitan areas.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.93-105
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• 2024

Car-sharing is a representative model of the sharing economy, and it is a service that rents or uses a car for the necessary time without owning a car. This industry is growing due to various factors such as technological advances, increasing awareness of environmental protection, and increasing demand for solving traffic congestion problems in cities. Accordingly, there is a need for a strategic approach for companies providing car-sharing services to respond quickly to market changes in order to expand market share and differentiate services. Accordingly, this study conducted a case study on open innovation activities between Gongcar and existing rental car companies, focusing on the research question "What effects do open innovation activities between car-sharing companies and existing rental car companies cause?" As a result of the study, it was confirmed that Gongcar have (1) the ability to actively respond to market fluctuations by establishing a flexible vehicle supply chain based on demand, (2) have significantly reduced growth capital expenditure (Growth Capex), and both cafe and rental car companies have (3) performed successful open innovation by improving key KPI indicators and recording financial performance. This study reveals how open innovation acts as a key business growth engine in the car-sharing industry, and its significance is found in that it empirically confirmed the successful implementation conditions of open innovation based on resource dependence theory.