This study investigates the seismic performance of beam-column connections using Thin-Walled Steel Composite (TSC) beams and Prestressed Reinforced Concrete (PSRC) columns. TSC beams are constructed from U-shaped thin steel plates that are filled with concrete, allowing for composite action with slabs through the use of shear connectors. They are widely applied in industrial buildings due to excellent strength, stiffness, and constructability. However, slender web plates are prone to local buckling, which may compromise their performance during seismic events. To mitigate this issue, internal supports have been introduced to enhance web stability and concrete confinement. Cyclic loading tests on three specimens—with and without internal supports—demonstrated that the supports increased moment capacity, improved energy dissipation, and effectively reduced buckling. Even slender sections demonstrated performance comparable to that of compact sections. All specimens reached peak strength at a 2.44% rotation angle, with damage localized near the supports. A practical connection detail was also proposed, taking into account constructability and structural reliability. The results provide valuable guidance for the seismic design of composite systems in large-scale structures.

The concept of resilience has gained increasing attention amid growing urbanization and rising vulnerability to infrastructure. While various methodologies exist for evaluating the resilience of lifeline systems, few address the distinct structural features and failure modes of railway networks. This study refines existing approaches by incorporating characteristics unique to high-speed railways, with a focus on two key aspects. First, we define the structure of railway networks by identifying nodes and links, and deriving link-specific resilience criteria based on the fragility characteristics and recovery profiles of their structural components. Second, we utilize real data from the Korean railway system to quantify the performance degradation caused by component failures during seismic events. To assess the framework’s applicability, we use a simplified network and a more complex one integrating Korea’s Honam Line and Honam High-Speed Line. The framework effectively identifies critical scenarios and provides a valuable tool for decision-makers in assessing seismic risk and planning recovery for railway infrastructure.

Conventional fixed-time traffic signal operations at urban intersections are typically based on prescheduled plans that presume stable and recurring traffic patterns, particularly during peak commuting hours. However, recent societal changes—including flexible work schedules, telecommuting, and evolving workweek structures—have introduced greater variability in traffic demand, thereby diminishing the effectiveness of traditional peak-hour-focused control strategies. This study investigated the performance of an AI-based adaptive traffic signal control system that operated independently of predefined time plans. A field demonstration was conducted in Jeju City, South Korea, where the system was deployed in both the cyclic and acyclic operation modes. By leveraging real-time traffic data obtained from AI-enabled video detectors, the system adjusted the signal timings on a per-second basis in response to dynamic traffic conditions. The performance was evaluated against the conventional time-of-day (TOD) control method under diverse traffic scenarios, including typical weekdays, weekends, and local event days. The AI-based system achieved substantial reductions in intersection delays—24.3% on weekdays, 22.2% on weekends, and 17.1% on event days—compared with the TOD baseline. Moreover, it preserved a comparable level of traffic progression (measured by the proportion of non-stop vehicle flows) even during acyclic operations. The greatest efficiency gains were observed during the nighttime and low-traffic periods, underscoring the capacity of the system to minimize unnecessary delays under variable conditions. These results highlighted the potential of AI-based adaptive signal control as a viable alternative to conventional fixed-time operations, offering enhanced responsiveness and operational flexibility in increasingly complex urban traffic environments. Future research will focus on scaling the system to larger networks and developing integrated optimization strategies across multiple intersections.

Current portable reference equipment used to evaluate the performance of vehicle detectors can collect traffic volume and speed only for the outermost lanes in each direction. Passing vehicles on the other lanes are manually counted by reviewing the recorded videos. Consequently, only traffic volume—without vehicle speed—is used as a reference value. This method is time-consuming for comparing the performance data from the equipment with the reference data and can compromise the performance evaluation. This study aims to enhance the efficiency of vehicle detection system (VDS) performance evaluations by developing multilane portable reference equipment that can accurately collect traffic information for lanes beyond the outermost lane or for more than two lanes. This study introduced the core technologies of multilane portable reference equipment and compared and analyzed the measurement accuracy of the developed equipment against data from fixed reference equipment operated by the Intelligent Transportation System (ITS) Certification and Performance Evaluation Center, following ITS performance evaluation criteria. The data from the fixed reference equipment were considered the true values, providing a basis for evaluating the accuracy of the measurements by the developed equipment. First, the accuracy of the vehicle length was determined by driving four test vehicles, each measuring 7,085 mm in length, 24–29 times in each lane. The accuracy was calculated by comparing the vehicle length data obtained from the fixed reference equipment with the actual vehicle length. A confidence interval was established for this accuracy. To assess the accuracy of the speed and occupancy time in relation to the accuracy of the analyzed vehicle length, we evaluated the error range of the vehicle length according to variations in speed and occupancy time. This analysis was based on the following relationship equation: “vehicle length = speed × occupied time – sensor spacing.” The analysis used data from approximately 16,000 vehicles, including the speed, occupancy time, and vehicle length, collected between 8:00 am and 12:00 pm on August 8, 2024. The principle behind measuring traffic volume and vehicle speed using multilane portable reference equipment involves detecting a vehicle by analyzing the time difference between the driver and passenger tires. The vehicle speed was calculated using the installation angle of the tire detection sensor and trigonometric functions. An analysis of the measurement accuracy revealed that the traffic volume accuracy of the outermost lane (the fourth lane) was 100% during both day and night. The speed accuracy was 98.8% during the day and 97.7% at night, representing the highest performance in these metrics. Additionally, the traffic volume accuracy for the innermost lane (the first lane), as measured by the detection sensor from the third lane, was more than 99.3% at all times, with a speed accuracy exceeding 96% during the day and night, that also demonstrated excellent results. The analysis results indicated that the multilane portable reference equipment developed in this study was suitable for evaluating the VDS performance. This equipment allowed the collection of traffic volume and speed data from all lanes, rather than only the outermost lanes. This capability enabled consistent analysis for each lane and enhanced efficiency by reducing the analysis time. Additionally, this is expected to improve the reliability of the performance evaluations.

본 연구는 동결융해 및 철근 부식으로 복합열화된 철근콘크리트 보를 탄소섬유 복합재료로 보강한 경우의 휨 거동을 평가하 기 위해 층상화 단면해석 모델을 제안하고 그 유효성을 실험적으로 검증하였다. 해석 모델은 열화에 따른 재료물성 저하와 CFRP 보강 효과를 통합적으로 고려하여 휨 거동을 예측하도록 구성되었다. 제안된 모델의 해석 결과, 열화 및 CFRP 보강 RC 보의 항복휨모멘트 와 최대휨모멘트 예측값은 실험값과 평균 1.01∼1.16의 비율을 보여 휨 성능을 매우 높은 신뢰도로 예측함을 확인하였다. 그러나 휨모 멘트-변위 관계에서는 일부 상이한 경향이 관찰되었다. 항복 이전 구간에서는 해석 모델의 휨 강성이 실험 결과보다 높게 평가되었는 데, 이는 해석 모델이 콘크리트의 초기 미세균열과 같은 비선형적 거동을 완벽히 반영하지 못하기 때문으로 분석된다. 반면, CFRP로 보강된 보의 항복 이후 구간에서는 해석 모델의 강성이 실험값보다 낮게 나타났다. 이는 현행 RC 이론 기반의 변위 산정 방식이 CFRP 보강재의 높은 탄성계수 효과를 충분히 반영하지 못하여 최대강도 도달 시의 변위를 과대평가하기 때문으로 판단된다.

This study proposes a methodology for predicting the physical properties such as the density of polymer composites, including asphalt binders, and evaluates its feasibility by identifying the quantitative relationship between the structure and properties of individual polymers. To this end, features are constructed using molecular dynamics (MD) simulation results and descriptor calculation tools. This study investigates the changes in the calculated density depending on the characteristics of the training dataset and analyzes the feature characteristics across datasets to identify key features. In this study, 2,415 hydrocarbon and binder-derived polymer molecules were analyzed using MD simulations and 2,790 chemical descriptors generated using alvaDesc. The features were pre-processed using correlation filtering, PCA, and recursive feature elimination. The XGBoost models were trained using k-fold cross-validation and Optuna optimization. SHAP analysis was used to interpret feature contributions. The variables influencing the density prediction differed between the hydrocarbon and binder groups. However, the hydrogen atom count (H), van der Waals energy, and descriptors such as SpMAD_EA_LboR consistently had a strong impact. The trained models achieved high accuracy (R² > 0.99) across different datasets, and the SHAP results revealed that the edge adjacency, topological, and 3D geometrical descriptors were critical. In terms of predictive accuracy and interpretability, the integrated MDQSPR framework demonstrated high reliability for estimating the properties of individual binder polymers. This approach contributed to a molecular-level understanding and facilitated the development of ecofriendly and efficient modifiers for asphalt binders.

콘크리트 구조물의 내ㆍ외부 보강재로 사용되는 CFRP(Carbon Fiber Reinforced Plastic) 그리드의 철근 대체 가능성을 확인하기 위해, 철도용 콘크리트 침목 내부에 CFRP 그리드를 보강한 후 유한요소 해석 프로그램인 ABAQUS를 활용하여 성능을 평가 하였다. 본 연구에서는 PC 강연선 대신 CFRP 그리드를 보강하고 하중을 재하한 결과, 피복두께 40 mm에서 최대 휨-인장 응력이 2.494 MPa로 도출되었으며 이는 KR CODE 2012의 허용응력 기준을 충족하는 값으로 나타났다. 추가적으로, 본 연구에서는 설계기준에 따라 하중 조건과 응력분포를 고려하여 중립축 위치와 CFRP 그리드의 배치를 최적화한 침목 단면설계를 진행하였다. ABAQUS 해석을 통해 침목의 휨 강도와 내구성을 평가한 결과, CFRP 그리드를 적용한 침목은 기존 PC 강연 선 보강 침목 대비 유사한 수준의 구조적 성능을 확보하면서도 경량화 측면에서 우수함을 확인하였다. 이를 통해 CFRP 그리드가 철근 을 대체하여 철도용 콘크리트 침목 설계에 적합한 보강재로 활용될 수 있음을 확인하였다.

This study proposes a methodology for predicting properties such as the density of polymer composites, including asphalt binders, and evaluates its feasibility by identifying the quantitative relationship between the structure and properties of individual polymers. To this end, this study investigates the variations in molecular dynamics (MD) results with molecular structural complexity and assesses the independence and correlation of variables that influence density. In this study, MD simulations were performed on hydrocarbon-based and individual asphalt binder molecules. The effects of various temperatures, molecular conditions, and structural features on the density were analyzed. MD-related variables influencing the calculated density were evaluated and compared with experimentally measured densities. The MD-calculated densities were used as target variables in a subsequent study, in which a machine learning model was applied to perform quantitative structure–property relationship analysis.The MD-calculated densities showed a strong correlation with experimental measurements, achieving a coefficient of determination of R2 > 0.95. Potential energy exhibited a tendency to cluster into 4–6 groups depending on the molecular structure. In addition, increasing molecular weight and decreasing temperature led to higher density and viscosity. Torsional energy and other individual energy components were identified as significant factors influencing both potential energy and density. This study provided foundational data for the property prediction of asphalt binders by quantitatively analyzing the relationship between the molecular structure and properties using MD simulations. Key features that could be used in the construction of polymer structure databases and AI-based material design were also proposed. In particular, the integration of MD-based simulation and machine learning was confirmed to be a practical alternative for predicting the properties of complex polymer composite systems.

본 연구는 팀 기반 시뮬레이션실습에서 교수평가, 동료평가와 자기평가의 점수를 확인하 며, 평가주체별로 점수를 어떻게 주는 경향이 있는지 알아보고 그 관계를 파악하는 것을 목적으로 한다. 이를 위해 ‘성인간호학실습(4)’를 수강한 간호대학생 중 연구 참여에 동의한 135명을 대상으로 학생들이 제출한 동료평가지와 자기평가지의 점수와 교수자 점수를 통계 적으로 분석하였다. 연구결과, 평가주체별 점수는 자기평가, 동료평가, 교수평가 순이었고, 자기평가에서 음의 왜도가 크고 첨도가 높아 스스로에게 높은 점수를 주는 경향이 있음과 집중된 평가 경향을 보이는 것으로 나타났다. 반면에 교수평가는 상대적으로 고르게 분포 된 평가를 하는 것으로 나타났다. 평가주체별 점수간 관계는 동료평가와 교수평가간에 정 적 상관관계가 있었다. 결론적으로, 팀 활동에서의 다면평가는 단일 평가자가 평가할 때 발 생하는 평가자 오류에서 상대적으로 자유롭지만, 단순히 평가자의 수를 늘리는 것만으로는 평가 결과의 신뢰성을 보장할 수 없기 때문에 맹목적으로 신뢰해서는 안 된다. 본 연구는 팀 기반 시뮬레이션실습에서 다면평가를 위한 구체적인 기준을 마련하고, 평가의 신뢰도와 타당도를 제고하기 위한 자료로 활용될 수 있을 것이다.

바이오차는 현재 토양개량제이자 탄소격리재로 사용되고 있으며, 건축산업에서 탄소격리에 관한 관심이 증가하고 있다. 본 연구에서는 목질계 바이오차를 시멘트 복합체에 함유하여 탄소격리효과의 가능성을 조사하는 것을 목표로 한다. 목질계 바이오차는 고탄소 물질로 수분을 흡수하는 특성이 있으며 시멘트 복합체에 함유하고자 할 때 시멘트와 비슷한 입도를 가져야한다. 혼입방법에 따라 바이오차를 함유한 시멘트 모르타르의 압축강도 특성을 평가하였으며, 시멘트를 바이오차로 1∼5% 치환하는 경우 Plain 대비 5∼12%까지 압축강도가 증진되는 것을 확인하였다.

Multivalent ions in natural aqueous solutions—such as seawater, brackish water, and freshwater—can negatively affect the performance of ion exchange membranes (IEMs) used in electrochemical energy and environmental devices. In this study, a pore-filling cation exchange membrane (CEM) permeable to multivalent ions was fabricated to minimize performance degradation caused by such ions. To achieve this, multilayer pore-filling CEMs were prepared by performing two impregnation processes using monomer electrolyte solutions of different compositions (varying deionized water content and monomerto- crosslinker ratios). As a result, a highly crosslinked electrolyte polymer formed on the internal side of the CEM, while a low-crosslinked polymer formed on the external side. Due to the presence of the low-crosslinked outer polymer layer, the multilayer pore-filling CEM exhibited a smaller increase in resistance caused by Mg2+ ions. Furthermore, based on the correlation between permselectivity and resistance measured in a 0.45 M NaCl + 0.05 M MgCl2 solution, which simulated the Mg2+ concentration in seawater, an optimal structure of multilayer pore-filling CEM was identified, and it exhibited a minimized increase in resistance and a permselectivity of over 90 %.

A high-pressure in-situ permeation measuring system was developed to evaluate the hydrogen permeation properties of polymer sealing materials in hydrogen environments up to 100 MPa. This system employs the manometric method, utilizing a compact and portable manometer to measure the permeated hydrogen over time, following high-pressure hydrogen injection. By utilizing a self-developed permeation-diffusion analysis program, this system enables precise evaluation of permeation properties, including permeability, diffusivity and solubility. To apply the developed system to high-pressure hydrogen permeation tests, the hydrogen permeation properties of ethylene propylene diene monomer (EPDM) materials containing silica fillers, specifically designed for gas seal in high-pressure hydrogen environments, were evaluated. The permeation measurements were conducted under pressure conditions ranging from 5 MPa to 90 MPa. The results showed that as pressure increased, hydrogen permeability and diffusivity decreased, while solubility remained constant regardless of pressure. Finally, the reliability of this system was confirmed through uncertainty analysis of the permeation measurements, with all results falling within an uncertainty of 11.2 %.

본 시험은 경상남도 진주시에 위치한 무가온온실에서 ‘신 틸라’ 남부하이부쉬 블루베리의 용기재배 시 피트모슬 대체 하여 코코피트를 사용할 수 있는 가능성을 평가하기 위하여 수행되었다. 피트모스+펄라이트(대조), 피트모스+코코피트 +펄라이트, 코코피트, 코코피트+펄라이트 등 네가지 조합으 로 구성되었으며 재식 이듬해 생육과 수량을 조사하였다. 그 결과, 주당 신초수는 대조구보다 코코피트 상토에서 21% 코 코피트+펄라이트 상토에서 43%나 감소하였고, 주당 수량은 대조구가 1.7kg인 반면, 코코피트 및 코코피트+펄라이트 상 토에서는 대조구의 41% 수준으로 현저히 낮았다. 또한 배액 의 pH는 대조구가 1월부터 수확 종료 후 1개월인 7월까지 3.8 에서 4.0 범위를 유지한 반면, 코코피트 단용 및 코코피트+펄 라이트 혼합 상토에서는 6 이상으로 상승하였다. 이러한 결과 코코피트 단독 또는 펄라이트 혼합만으로는 블루베리 생육에 부적합하며, 기존 피트모스+펄라이트 상토에 일부 혼합하여 사용하는 경우에만 활용 가능함을 시사한다.

In apartment buildings in Korea, irregular walls, such as T-, L-, and U-shaped walls, are commonly used. However, in practical design, the geometric irregularities of walls are often neglected when determining the length of the lateral confinement region. Further, although earthquake loads apply from various directions, the lateral confinement region is typically determined for the in-plane direction of the web. Thus, using finite element analysis, this study investigated the structural performance of irregular walls subjected to various loading directions. As the design parameters, wall shape, cross-sectional aspect ratio, and loading direction were addressed. According to the parametric analysis results, as the length of flange in tension increased, the lateral confinement region should be evaluated with consideration of the geometric irregularity. Further, for the L- and U-shaped walls, it is recommended to evaluate the lateral confinement region for various loading directions. Based on these results, a design method to determine the lateral confinement region of irregular walls was suggested.

In the United States, seismic design standards are crucial in classifying buildings into Risk Categories I to IV. These categories are based on the buildings' occupancy type and the potential risk they pose to public safety, the protection of human life, and the socioeconomic consequences of structural collapse in the event of an earthquake. As the risk category increases, a higher seismic importance factor and more stringent drift limits are imposed on the respective building. This results in enhanced lateral strength and stiffness of the seismic force-resisting system. This study, which compares the seismic demands of special moment frame buildings assigned to high-risk categories, focusing on static system overstrength, ductility, and collapse risk, provides practical insights for structural engineers and architects. For this purpose, nonlinear static and dynamic analyses are performed to quantify the seismic demands of 18 steel frame buildings assigned to Risk Categories II, III, and IV. The findings indicate that buildings in Risk Category II do not meet the target collapse risk of 1% in 50 years, as specified in ASCE/SEI 7. For buildings in higher risk categories, the equivalent lateral force method for estimating seismic base shear is deemed more effective in ensuring adequate seismic performance.

The cosmetics industry expects low irritation and skin improvement effects by utilizing natural ingredients and botanical extracts. In particular, Poncirus trifoliata fruit extract is a traditionally recognized ingredient with proven pharmacological efficacy and contains various bioactive compounds. According to previous studies, Poncirus trifoliata fruit has been reported to possess antioxidant, whitening, and skin-improving effects. In this study, the antioxidant and whitening efficacy of Poncirus trifoliata fruit extract was evaluated according to different extraction solvents, and the formulation stability of a cleanser containing this extract was analyzed. The antioxidant activity of Poncirus trifoliata fruit extract was confirmed by measuring DPPH and ABTS⁺ radical scavenging activity, while its whitening efficacy was assessed through tyrosinase inhibition activity. Additionally, the total polyphenol and flavonoid content was measured, confirming its strong antioxidant effects. These findings suggest that Poncirus trifoliata fruit extract may contribute to anti-aging and skin-whitening effects. To evaluate the stability of a cleansing formulation containing Poncirus trifoliata fruit extract, pH and viscosity changes were measured over 28 days under temperature conditions of 5°C, 25°C, and 45°C. The results indicated a decline in stability over long-term storage. Therefore, further studies are required to optimize the extract concentration and improve the formulation for enhanced long-term stability. This study suggests that Poncirus trifoliata fruit extract has potential as a functional cosmetic ingredient for skin whitening and anti-aging and can serve as fundamental data for future research on stability enhancement.

Environmental DNA (eDNA) has emerged as a promising tool for aquatic biodiversity monitoring, yet its collection in lentic ecosystems remains technically constrained by filtration capacity and field logistics. In this study, we applied a novel eDNA concentration system, QuickConcTM, to evaluate freshwater mussel diversity in lakes, and compared its performance with the conventional GF/F filtration method. Water samples were collected from four reservoirs at surface, mid, bottom, and waterside layers, and processed using both filtration techniques. Metabarcoding of mitochondrial 16S rDNA revealed that QuickConcTM captured a higher average number of amplicon sequence variants (ASVs) and exhibited greater species richness and diversity indices (Shannon and Simpson), although the differences were not statistically significant. QuickConcTM samples showed a greater capacity to detect rare taxa and to recover higher ASV richness in certain cases, suggesting its potential to enhance biodiversity resolution. Species composition remained consistent across methods, with Cristaria plicata and Sinanodonta lauta being dominant in both cases. However, slight spatial variations in species assemblages were observed between center and waterside sampling points, highlighting the influence of habitat heterogeneity on eDNA distribution. Overall, our results demonstrate that the QuickConcTM system offers a practical and efficient alternative to traditional filtration methods for eDNA-based freshwater mussel monitoring, particularly in environments with high suspended solids. The findings underline the need for adaptive sampling strategies that consider both methodological and ecological factors when designing eDNA surveys in lentic ecosystems.

전 세계적으로 생물다양성을 보호하기 위한 방법으로 보호지역을 지정하고 있지만, 보호지역에 대한 관리 부족으로 효과성을 평가하기 어렵다. 보호지역 효과성 평가를 위해 다양한 지표들을 이용하여 평가하고 있다. 그 중 토지피복 변화 분석은 경제적이고 장기적인 변화 파악이 가능하며, 공간적 제한이 상대적으로 적어 다양한 대상지에서 활용할 수 있다는 장점이 있다. 본 연구에서는 토지피복 변화를 이용하여 야생생물 보호구역의 효과성 평가를 목적으로 한다. 보호지역 내부와 외부, 타 보호지역과의 중복지정 여부, 지정 시기에 따라 과거 자연지역이 농업지역 또는 시가화건조지 역으로 변화한 비율을 분석하였다. 연구 결과로 첫째, 보호지역 내부에서는 보호 효과가 있지만, 외부에서는 개발압력이 있음을 알 수 있다. 둘째, 타 보호지역과 중복된 보호지역일수록 효과가 있음을 알 수 있다. 셋째, 지정 시기가 오래된 보호지역일수록 시간이 지남에 따라 토지피복 변화가 줄어들어 지속적인 효과가 있음을 알 수 있다. 본 연구는 경제적이 고 장기적 변화 파악이 가능한 토지피복을 이용하여 보호지역의 효과성을 정량적으로 평가했다는 점에 의의가 있다. 토지피복은 끊임없이 변화할 것이며, 드론과 같은 첨단장비를 이용하여 실시간 모니터링을 한다면 보호지역의 효과와 압력을 더욱 신속하고 정밀하게 평가할 수 있을 것이다.

본 연구는 중·소규모 사업장의 높은 산업재해를 저감하기 위한 목적으로 자 기규율 예방체계의 위험성평가를 개선하는 방안을 연구하였다. 이론적 고찰을 위해 기존의 위험성평가 방법과 문제점을 파악하였고, 대기업에 비하여 열악한 중·소규모 사업장의 위험성평가수행에 어려움을 인식하였다. 이를 해결하 기 위한 수단으로 중·소규모 사업장의 지속 가능한 발전을 위해 ESG 경영 평가지표를 함께 고찰하였다. ESG 평가지표 중 산업안전 분야의 위험성평가 내용이 일부 존재하여 기존 위험성평가와 ESG 평가지표 간 관계성, GAP분석 을 통해 문제점을 발견하고 리스크마이닝 기법으로 개선방안을 제안하였다. 모든 사업장에 적용가능한 고도화된 자기규율 예방체계의 위험성평가 개선방 안으로 향후 중소규모 사업장의 산업재해를 경감시키는데 중요한 역할을 할 것으로 기대한다.

Autonomous vehicle (AV) technology is rapidly entering the commercialization phase driven by advancements in artificial intelligence, sensor fusion, and communication-based vehicle control systems. Real-world road testing and pilot deployments are increasingly being conducted, both domestically and internationally. However, ensuring the safe operation of AVs on public roads requires not only technological advancement of the vehicle itself but also a thorough pre-evaluation of the road environments in which AVs are expected to operate. However, most previous studies have focused primarily on improving internal algorithms or sensor performance, with relatively limited efforts to quantitatively assess how the structural and physical characteristics of road environments affect AV driving safety. To address this gap, this study quantitatively evaluated the compatibility of road environments for AV operation and defined the road conditions under which AVs can drive safely. Three evaluation scenarios were designed by combining static factors such as curve radius and longitudinal gradient with dynamic factors such as level of service (LOS). Using the MORAI SIM autonomous driving simulator, we modeled the driving behaviors of autonomous vehicles and buses in a virtual environment. For each scenario, the minimum time to collision (mTTC) from the moment the AV sensors detected a lead vehicle was calculated to assess risk levels across different road conditions.The analysis revealed that sharper curves and lower service levels resulted in significantly increased risk. Autonomous buses exhibited a higher risk on downhill segments, autonomous vehicles were more vulnerable to uphill slopes and gradient transitions. The findings of this study can be applied to establish road design standards, develop pre-assessment systems for AV road compatibility, and improve AV route planning and navigation systems, thereby providing valuable implications for policy and infrastructure development.