PURPOSES : This study aims to provide societal benefits that demonstrate the effectiveness of remodeling projects, thereby providing a basis for activating and systematically and continuously promoting remodeling projects METHODS : Using the International Roughness Index (IRI) and World Bank's HDM-4, a model for vehicle operating costs was estimated. The change in vehicle operating costs was calculated by inputting the pre- and post-remodeling IRI values into the estimated model. Additionally, the future IRI over the life cycle was derived using the results of a study on the changes in pavement conditions between conventional and remodeling methods. The vehicle operating costs for different maintenance alternatives were compared by inputting them into the estimated model. RESULTS : The improvement in road smoothness after the project resulted in an annual vehicle operating cost benefit of approximately 1.6 billion won, with an estimated benefit per kilometer of approximately 64 million won. Furthermore, a comparison of vehicle operating costs for maintenance alternatives over the life cycle revealed that the remodeling method led to savings of 2.1 billion won compared with conventional methods. CONCLUSIONS : The findings of this study will serve as fundamental data supporting the necessity and justification for remodeling projects, particularly in the current scenario, where the need for maintenance of existing roads exhibits a faster growth trend than the extension of new roads. Additionally, this study could be supplemented by further research focusing on the consideration of pavement conditions in unit cost estimation and additional benefit estimation studies tailored to remodeling projects.

PURPOSES : This study aimed to predict the number of future COVID-19 confirmed cases more accurately using public and transportation big data and suggested priorities for introducing major policies by region. METHODS : Prediction analysis was performed using a long short-term memory (LSTM) model with excellent prediction accuracy for time-series data. Random forest (RF) classification analysis was used to derive regional priorities and major influencing factors. RESULTS : Based on the daily number of COVID-19 confirmed cases from January 26 to December 12, 2020, as well as the daily number of confirmed cases in Gyeonggi Province, which was expected to occur on December 24 and 25, depending on social distancing, the accuracy of the LSTM artificial neural network was approximately 95.8%. In addition, as a result of deriving the major influencing factors of COVID-19 through random forest classification analysis, according to the number of people, social distancing stages, and masks worn, Bucheon, Yongin, and Pyeongtaek were identified as regions expected to be at high risk in the future. CONCLUSIONS : The results of this study can help predict pandemics such as COVID-19.

PURPOSES : This study sought ways to connect urban above ground roads and underground roads to utilize urban space more efficiently in the development of underground roads, which are currently under development in order to alleviate problems caused by oversaturated above-ground roads. A simulation analysis was performed to develop an operation strategy that connects above-ground and underground roads to prevent congestion in above-ground areas such as entrances and exits from transferring to underground roads as well as to present its effectiveness. METHODS : Traffic efficiency analysis according to the operation strategy of above ground and underground roads was conducted using VISSIM, a microscopic traffic simulation software. The functions implemented in VISSIM were collected to set effectiveness analysis indicators for each underground road operation strategy. The Shinwol-Yeoui Underground Road was selected as the spatial scope of this study, and a surrounding road network was constructed. In addition, full-scale simulation analysis preparations were completed by performing network calibration based on the actual traffic attribute data of underground and surrounding surface roads within the construction scope. Accordingly, a traffic efficiency evaluation analysis was conducted based on the underground road operation strategy. CONCLUSIONS : Information on the increase in traffic volume within the Shinwol-Yeoui underpass was collected every 15 min. The analysis was divided into an analysis of the traffic situation within the underpass through demand control when the service level reached level D and an analysis of when demand control was not performed. It was found that demand control was necessary for the Shinwol-Yeoui Underpass when the internal traffic volume reached 2,500 vehicles/h. In addition, to analyze the spread of traffic and congestion owing to the weaving phenomenon caused by lane changes in the underpass, an analysis was conducted to observe the traffic improvement effect when full lane changes are possible for the Shinwol-Yeoui Underground Road, which currently has some lane-change-permitted sections. The analysis showed that both the maximum traffic volume and average travel speed showed better results when lane changes were allowed, and the communication situation at Yeoui JCT was found optimal.

본 연구는 OSM 데이터를 활용하여 북한 도시별 도로망 데이터를 수집하고 OSMnx을 적용하여 도로망 네트워크의 공간패턴을 분석하였다. 분석 결과, 도로망의 특성에 있어서 도시 간의 격차를 확인하였다. 이와 함께 도로 밀도를 이용한 군집분석을 통해 유사한 특징을 갖는 도시들을 확인하였고, 도로망의 방향성 분석을 이용해서 많은 도시가 무질서함이 높은 방사형 패턴을 확인하였 다. 그동안 분석이 어려웠던 북한의 도로망에 대해, 본 연구는 OSM 데이터를 이용하여 자료를 수집하고 북한 도시들의 도로망 패턴을 분석했다는 점에서 연구의 의미가 있다.

PURPOSES : Pavement surface friction depends significantly on pavement surface texture characteristics. The mean texture depth (MTD), which is an index representing pavement surface texture characteristics, is typically used to predict pavement surface friction. However, the MTD may not be sufficient to represent the texture characteristics to predict friction. To enhance the prediction of pavement surface friction, one must select additional variables that can explain complex pavement surface textures. METHODS : In this study, pavement surface texture characteristics that affect pavement surface friction were analyzed based on the friction mechanism. The wavelength, pavement surface texture shape, and pavement texture depth were hypothesized to significantly affect the surface friction of pavement. To verify this, the effects of the three abovementioned pavement surface texture characteristics on pavement surface friction must be investigated. However, because the surface texture of actual pavements is irregular, examining the individual effects of these characteristics is difficult. To achieve this goal, the selected pavement surface texture characteristics were formed quantitatively, and the irregularities of the actual pavement surface texture were improved by artificially forming the pavement surface texture using threedimensionally printed specimens. To reflect the pavement surface texture characteristics in the specimen, the MTD was set as the pavement surface texture depth, and the exposed aggregate number (EAN) was set as a variable. Additionally, the aggregate shape was controlled to reflect the characteristics of the pavement surface texture of the specimen. Subsequently, a shape index was proposed and implemented in a statistical analysis to investigate its effect on pavement friction. The pavement surface friction was measured via the British pendulum test, which enables measurement to be performed in narrow areas, considering the limited size of the three-dimensionally printed specimens. On wet pavement surfaces, the pavement surface friction reduced significantly because of the water film, which intensified the effect of the pavement surface texture. Therefore, the pavement surface friction was measured under wet conditions. Accordingly, a BPN (wet) prediction model was proposed by statistically analyzing the relationship among the MTD, EAN, aggregate shape, and BPN (wet). RESULTS : Pavement surface friction is affected by adhesion and hysteresis, with hysteresis being the predominant factor under wet conditions. Because hysteresis is caused by the deformation of rubber, pavement surface friction can be secured through the formation of a pavement surface texture that causes rubber deformation. Hysteresis occurs through the function of macro-textures among pavement surface textures, and the effects of macro-texture factors such as the EAN, MTD, and aggregate shape on the BPN (wet) are as follows: 1) The MTD ranges set in this study are 0.8, 1.0, and 1.2, and under the experimental conditions, the BPN (wet) increases linearly with the MTD. 2) An optimum EAN is indicated when the BPN (wet) is the maximum, and the BPN decreases after its maximum value is attained. This may be because when the EAN increases excessively, the space for the rubber to penetrate decreases, thereby reducing the hysteresis. 3) The shape of the aggregate is closely related to the EAN; meanwhile, the maximum value of the pavement surface friction and the optimum EAN change depending on the aggregate shape. This is believed to be due to changes in the rubber penetration volume based on the aggregate shape. Based on the results above, a statistical prediction model for the BPN (wet) is proposed using the MTD, EAN, and shape index as variables. CONCLUSIONS : The EAN, MTD, and aggregate shape are crucial factors in predicting skid resistance. Notably, the EAN and aggregate shape, which are not incorporated into existing pavement surface friction prediction models, affect the pavement surface friction. However, the texture of the specimen created via three-dimensional printing differs significantly from the actual pavement surface texture. Therefore, the pavement surface friction prediction model proposed in this study should be supplemented with comparisons with actual pavement surface data in the future.

In this paper, in order to study the relationship between the safety culture of highway management agencies and disaster reduction activities (BCMS), a measurement tool was identified through previous research on safety culture, and the validity of the measurement tool was confirmed through exploratory factor analysis. I want to check. The subjects of the study were workers belonging to disaster reduction activity management system certification organizations among highway management organizations. The highway management agencies are the Korea Expressway Corporation, which manages the functional continuity of national highways nationwide, and 8 of the 21 private road agencies that manage the functional continuity of the highways. The safety culture measurement tool is an indicator that measures safety culture factors, and is reorganized by the researcher based on survey items from previous studies, with management/manager safety values and attitudes, safety communication, safety education and training, and safety regulations/ management system as subfactors. A total of 24 questions were comprised of the survey tool. As a result of the study, the result of exploratory factor analysis was that the safety culture scale was extracted into four factors based on theoretical grounds, and the total cumulative variance was 80.360%. When checking the questions for each factor, it was found that all the questions loaded on the factor that was originally intended to be measured. Factor 1 is management, factor 2 is safety, and factor 3 is communication., Factor 4 was named education. Number of questions: 4 management questions, 3 safety questions, communication It consisted of 4 questions and 2 education questions.

스펀지 도시는 도시가 물을 효율적으로 사용한다는 개념을 강조한다. 도로의 스펀지화는 스펀지 도시 의 가장 직접적인 구현이며, 도시의 침수 및 물 부족 문제를 해결할 수 있다. 본 연구에서는 지닝시 성화 로를 대상으로 하여 성화로 이용에 대한 인식 및 개선수요를 분석하기 위하여 성화로 주민, 환경미화원, 지닝시 택시운전자 및 도로 계획가를 대상으로 현장 인터뷰 및 설문조사를 실시하였다. 조사내용을 바 탕으로 성화로 이용빈도에 대한 인식과 인구통계학적 특성의 유의성을 검증하기 위해 교차분석을 수 행하였다. 선행연구와 성화로 이용 인식분석을 통해 스펀지형 도로, 친환경 생태도로 및 안전형 도로의 3대 도로유형을 설정하였다. 도로유형의 각 항목의 중요도가 성화로침수에 미치는 영향관계를 결정하 기 위해 선형회귀분석을 수행하였으며, 성화로 개선의 방향을 결정하기 위해 AHP 계층분석법을 이용 하여 가중치를 계산하여 각 항목의 중요도 점수를 분석하였다. 분석결과 성화로는 LID 기술, 생태형 비 탈면 설계 및 식생배치가 도로 스펀지화 개선의 주요방향임을 알 수 있다.