• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.170-181
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• 2015

This study explores passengers' travel characteristics at six bus stops on the Seoul Ring Expressway using smart traffic card data. Based on the characteristics, political strategies to improve bus facilities on expressway are suggested. Firstly, among them two bus stops of Guri and Uiwang-Cheonggye have higher transfer rate of passengers, 37.56% and 36.9% of the total intercity (red) bus passengers on the expressway, respectively. Secondly, Uiwang-Cheonggye bus stop has the highest transfer rate, and Guri bus stop has also higher transfer rate and the highest on-and-off passengers. It implies that both bus stops need to be prioritized for improving bus stop facility, access roads, and connection facility between the bi-directional stops. Thirdly, Guri (down) bus stop has relatively longer waiting time for transfer, thus shorter bus headways running the bus stop should be considered. Lastly, most passengers using both stops come to and from Bundang-gu in Geongnam City. Overall, the results of this study would be helpful for transport planners to develop effective bus route policies and bus operation.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.819-829
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• 2022

Professional baseball is one of the spectator sports that has been loved for a long time by the citizens as a recreational activity since its establishment in 1982, and has been playing pivotal role as a national sport. However, there has been decline in the number of audiences since 2019. Hence, this research paper aimed to provide strategic direction for planning and improvement of professional baseball stadiums by applying the concept of servicescape. In this research, five key factors of servicescape that affects players performance and the level of immersion of spectators were derived through literature review, and based on these key factors, case study analysis were carried out for 51 domestic and foreign baseball stadiums while focusing on the factors derived. Domestic baseball stadiums highly concentrate on spectatorship without effectively responding to change in spectators demand and its effective use of space rather than baseball games. As in foreign cases, it is critical to modify mangement process and planning direction, and improve policies while perceiving baseball stadium as recreational and cultural space.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.157-171
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• 2021

As smartphones spread and ICT technologies develop, taxi services have changed from hovering to platform-based calls and reservations. This has improved the mobility and accessibility of taxi users but caused problems, such as digital observing (no-responses to calls) for either short-distance services or services during the peak-demand periods. Digital Observing means ignoring and not accepting calls when they occur, which require improvement. Therefore, this study aims to derive measures to mitigate discrepancies in taxi supply and demand by adjusting the expected revenue of each taxi service using reinforcement learning based on the Taxi operation data. The results confirmed that the average complete response rate to calls would increase from 50.29% to 54.24% when incentives are applied, and an improvement of 5.86% can be achieved in short-distance sections of less than 5,000 won incentives. It is expected that the improvement will increase profitability for drivers, reduce the waiting time for passengers, and improve satisfaction with taxi services overall.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.25-31
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• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.351-363
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• 2022

Purpose: The objective of this research is to find manufacturing employment clusters of the disaster safety sector in South Korea. Method: The LISA(Local Indicator of Spatial Association) analysis method is applied to the employment data of 229 local governments categorized by the 2019 Korean Standard Industry Classification and Disaster Safety Industry Special Classification. The LISA method identifies the spatial dependency of employment and the spatial cluster of industries. Result: Three research findings are summarized. First, employment of the disaster safety industry in South Korea occupies about six percent of the total manufacturing industry. The annual proportion is in increasing trend. Second, the employment cluster of the disaster safety industry is located in the western side of the Seoul metropolitan region. Third, manufacturing businesses of industrial safety goods preventing industrial accidents are concentrated in regions of Busan, Ulsan, Changwon, Gyeongnam, and Gimhae, where heavy and chemical industries and industrial complexes are formed. Conclusion: Investment and promotion policies are suggested to the manufacturing employment clusters of the disaster safety industry for fostering these regions. Research results can be used to the better policies for industrial development and employment improvement of manufacturing clusters of the disaster safety industry in South Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.233-252
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• 2022

Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.383-394
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• 2023

Purpose : This study focuses on improvements in cell broadcast service(CBS) with consideration of socially vulnerable groups, and identifies service factors necessary for elderly people in particular. Method : Multiple regression analysis was applied to test overall satisfaction with cell broadcast service as the dependent variable and each of the service factors as the independent variable. Result : The results showed that fast delivery had the greatest effect on overall satisfaction with cell broadcast service in both groups, followed by the delivery of sufficient content for the elderly group and system quality for the non-elderly group. The results demonstrated that the elderly group cared more about information content, while the non-elderly group considered functions such as system quality and text message transmission criteria more important. Conclusion : Elderly people consider the delivery of sufficient information important as well as fast delivery, which suggests that it is necessary when sending cell broadcast service to give consideration to the characteristics of elderly people, as they tend to have weaker understanding and thinking abilities than the non-elderly.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.21-36
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• 2023

Activity-based modeling systems have increasingly been developed to address the limitations of widely used traditional four-step transportation demand forecasting models. Accordingly, this paper introduces the Activity-BAsed Traveler Analyzer (ABATA) system. This system consists of multiple components, including an hourly total population estimator, activity profile constructor, hourly activity population estimator, spatial activity population estimator, and origin/destination estimator. To demonstrate the proposed system, the emission impact of land use changes in the 5-1 block Sejong smart city is evaluated as a case study. The results indicate that the land use with the scenario of work facility dispersed plan produced more emissions than the scenario of work facility centralized plan due to the longer travel distance. The proposed ABATA system is expected to provide a valuable tool for simulating the impacts of future changes in population, activity schedules, and land use on activity populations and travel demands.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.49-74
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• 2010

Cities are major sources of greenhouse gas emissions but also suitable places for implementing proactive climate mitigation and adaptation strategies. Based on the interdisciplinary review of literature, we categorize the current discussion about urban climate mitigation and adaptation planning, policy and practices into four perspectives - sustainability science, global change science, multilevel governance, and structural engineering. While these four schools of thought have distinct perspectives rooted in different disciplinary lenses, our synthesis of the literature identifies several universal themes that are common to all of the perspectives in the context of combating threats posed by climate change. The Portland case study illustrates that a city can make changes to reduce greenhouse gas emissions and increase adaptive capacity to climate change impacts by implementing smart growth, devising local climate action plans that target emission reductions in various sectors, recognizing the interactions and influences of multiple scales of governance, and supporting the installation of various green infrastructures that contribute to green economy. Furthermore, a university can serve as a hub in this climate mitigation and adaptation arena by connecting various levels of community organizations in both public and private sectors, creating innovative research centers and spatially explicit green infrastructure, designing impact assessments and campus carbon inventories, and engaging students and the larger community through service learning.