The integrity of interlayer bonding in asphalt pavements is a critical factor to ensure the structure behaves as a unified, monolithic system. Common issues like dust contamination on the receiving surface and inadequate tack coat application create weak interfacial planes that promote localized shear deformation specifically in high-traction zones like braking and turning areas. This study introduces a transferable framework that integrates lab-based interlayer bond characterization, composite fatigue testing, and finite element (FE) modeling to assess pavement performance under realistic field conditions.Two tack coats were used in this study, including regular tack coat (RSC-4) and clean tack coat (ILT-4) and considered 0%, 50% (remaining 50% was covered with dust), and 100% of the contact surface area, at three distinct tack coat application rates. Peak shear strength, initial stiffness, and fractured energy were determined from monotonic shear tests for quantifying bonding state and for FE simulations. Four-point bending (4PB) test was used to characterize fatigue performance, using normalized stiffness s(N), fatigue life and mid-life degradation rate or damage rate (DR). To relate the findings with field behavior, FE simulations estimate shear demand during braking, allowing a demand-to-capacity comparison. Results indicate that dust samples have 10%-30% lower bonding strength and must reach shear fail at the service life at the breaking zone with -0.93 midlife damage rate. Considering DR as a primary performance indicator, the framework provides the ultimate recommendations such as ensure surface cleanliness, uniform tack coat application, and quality control in high-stress zones.

도로 운송 부문은 전 세계 에너지 관련 온실가스 배출의 약 23%를 차지하며, 전 세계적인 물류 수요 증가와 도시화로 인 해 향후에도 지속적인 증가 추이를 보일 것으로 예측된다. 이러한 기후 위기 상황에서 차량의 연비를 개선하여 탄소 배출량 을 저감하기 위한 기술적 노력이 다각도로 진행되고 있다. 이 중 도로 포장과 차량 간의 복잡한 물리적 상호작용인 Pavement-Vehicle Interaction(PVI)은 포장체의 처짐으로 인해 발생하는 추가 연료 소모량(Excess Fuel Consumption, EFC)을 결정하는 핵심적인 요소로 주목받고 있다. 본 연구는 도로 포장과 차량의 상호작용으로 인해 발생하는 추가 연료 소모량을 산정함에 있어, 포장 재료의 에너지 소산 특성을 정의하는 감쇠 모델과 하중 하단에서의 포장 처짐 기울기를 계산하는 경사도 산정 방법이 미치는 영향을 정량적으로 비교 분석하였다. 구체적으로, 점성 감쇠 모델과 이력 감쇠 모델을 각각 적용하여 포장의 동적 응답을 도출하였다. 또한, 기 존의 선형 및 상수 기반 경사 산정 방식의 한계를 극복하기 위해, 본 과업에서 제시하는 하중 재하 지점의 순간 기울기를 산정하는 수치적 방법론을 검토하였다. 해석 결과, 선택된 감쇠 모델의 종류와 경사도 산정 방식의 조합에 따라 최종적으로 도출되는 연료 소모량 산정 결과에 유의미한 수치적 차이가 발생함을 확인하였다. 특히 이력 감쇠 모델과 순간 기울기 방식 의 결합은 기존 모델들이 간과했던 포장체의 비대칭적 처짐 거동을 더욱 정밀하게 포착함으로써, 보다 현실적인 탄소 배출 량 예측 근거를 제시하였다

Recent tactical vehicle development has focused on balancing protection and mobility through reinforced hulls, modular armor, and advanced mission systems. These upgrades have inevitably increased the gross vehicle weight (GVW), demanding higher engine performance to maintain mobility. This study analyzes the relationship between GVW, engine power, and power-to-weight ratio (P/W) across various international tactical and MRAP vehicles to assess how technological progress has compensated for weight growth. The GVW– power correlation illustrates generational trends in powertrain scaling, while the GVW–P/W analysis reveals changes in mobility efficiency as protection and payload increased. Results indicate that although engine outputs have risen in proportion to GVW, the overall P/W ratio has gradually declined, implying a design shift toward protection-oriented configurations. From these findings, a reference range of 20–25 hp/t is suggested as an appropriate target for future 4×4 and medium-class tactical vehicles. The results provide a quantitative basis for achieving an optimal balance between protection, payload capacity, and mobility in next-generation military vehicle design.

Modern warfare demands a high level of coordination and interoperability among multiple combat vehicles and crew members operating in dynamic and complex environments. Traditional training methods are often limited in scalability, flexibility, and cost-efficiency, making it challenging to effectively prepare forces for future battlefield scenarios. To address these limitations, this study presents the development of a Multiple Combat Vehicle Integrated Training Device, a next-generation simulation-based training system. The MCITD integrates advanced technologies such as Extended Reality, Digital Twin modeling, and Artificial Intelligence to deliver immersive, interactive, and highly realistic training experiences. The system allows for simultaneous training of multiple crew members in a networked environment that replicates real-world combat conditions, including terrain, weather, and adversary behavior. Key system components, including the simulation module, network communication framework, battlefield environment generator, and performance analysis engine, are discussed in detail. Potential application scenarios such as large-scale land operations, urban warfare, and multinational joint training exercises are also explored. The MCITD aims to enhance combat readiness, mission success, and training efficiency by providing a cost-effective, scalable, and adaptable solution for future-oriented military training programs.

This paper presents the design and experimental validation of an intelligent tire alignment and lifting control system for an under-vehicle autonomous parking robot. The proposed system enables the robot to autonomously enter beneath a vehicle, recognize tire positions using a LiDAR-based sensing module, and perform precise lifting through a fork-type mechanism. A YOLOv8 instance segmentation algorithm is employed to detect tire regions from LiDAR point cloud data and estimate their geometric centers. The detected tire positions are then matched with a vehicle database to determine the correct alignment for lifting. Experiments were conducted on three different vehicle types under various surface conditions. The results show that the proposed system achieved a tire recognition accuracy exceeding 95%, a lifting success rate of 100%, and an average lifting operation time of 12.3 seconds. These results demonstrate the reliability and practicality of the proposed method for real-world autonomous parking applications.

This study aims to evaluate the high-precision positioning capability and lane-level localization accuracy of low-cost RTK-GNSS(Real- Time Kinematic Global Navigation Satellite System) technology. This study compares the positioning accuracy and lane-level localization performance of a low-cost RTK-GNSS module with those of a commercial high-precision receiver under identical conditions. Specifically, the root-mean-square, lateral offsets from HD-map(High-Definition Map) lane centerlines, and lane-change detection rates were evaluated to examine the applicability of the module to advanced mobility systems. Based on experiments conducted using a two-axis linear motion device and actual-vehicle tests on expressways, the low-cost RTK-GNSS module demonstrated precision positioning and lane-level localization comparable to that of a commercial high-precision receiver under the same test conditions. In the precision-positioning evaluation, the maximum positioning error of the low-cost module is approximately 2 cm, which is larger than that of a commercial receiver. Nevertheless, its average error generally remained within the typical range of 1–2 cm, which is the expected range for fixed RTK solutions in opensky environments. Furthermore, the difference in the lane-level localization accuracy between the low-cost and high-precision modules remained at approximately 1 cm. Although the low-cost RTK-GNSS module employs fewer receiver channels compared with commercial high-precision units, the integration of the RTK-OMEGA solution, which supports robust integer ambiguity resolution and is a key element of RTK correction, enables it to perform comparably to a commercial module under identical test conditions. The performance-evaluation indicators and methodologies presented herein are expected to provide a meaningful foundation for future studies aimed at ensuring the reliability and safety of cost-effective RTK-GNSS technologies.

This study proposes a lightweight algorithm for real-time front-vehicle detection using low-resolution camera footage under various driving conditions. The proposed method first extracts driving lanes using Canny edge detection and the Hough transform, thus enabling efficient lane detection. A forward region of interest (ROI) is delineated based on the extracted lane geometry. Subsequently, YOLOv11 is employed to detect vehicles within each frame, where only those located inside the defined ROI are classified as preceding vehicles. To evaluate the applicability of the proposed method in diverse environments, its performance was assessed across six driving scenarios: normal driving, traffic congestion, complex structural environments, nighttime, tunnel sections, and sharp curves. Experimental results show that the proposed approach maintains a stable detection accuracy across different conditions while offering a low computational cost and a high processing speed. Compared with segmentation-based deep-learning lane-detection models, the proposed method demonstrates superior real-time capability and can operate using only a built-in monocular camera without relying on expensive sensors such as LiDAR, radar, or artificial markers. This study serves as a foundation for vision-based ADASs, front-vehicle-following control, and road-hazard detection systems.

This study aims to quantitatively and qualitatively evaluate the operational effects of an emergency-vehicle preemption (EVP) system implemented in Anyang City and to derive improvement directions based on both empirical performance outcomes and user-experienced insights. Specifically, this study integrates three complementary methodologies: (1) controlled field tests comparing pre- and post-EVP travel performance under consistent traffic and signal conditions, (2) a one-year operational evaluation using 204 actual dispatch cases collected from six 119 Safety Centers, and (3) a structured survey of frontline firefighters who directly utilized the EVP system during actual emergency responses. The field test results indicated that the average travel time reduced by approximately 44% while the average travel speed increased by approximately 79%, with paired t-test verification confirming that the observed improvements were statistically significant and attributable to the EVP system instead of to random variations. Similarly, the operational evaluation indicated that the actual travel time reduced by an average of 49% compared with navigation-estimated values, whereas the golden-time (5 min) arrival rates for both fire/rescue and medical dispatches exceeded the regional average, with consistent performance demonstrated even under varying travel distances and road complexities. The firefighter survey further reinforced these findings, with respondents reporting clear improvements in golden-time achievement, reduced anxiety toward potential safety risks, and enhanced perceived safety during emergency trials, as well as identified several practical limitations such as route mismatches, occasional system malfunctions, and difficulty in perceiving preemption activation—factors that suggest necessary technical and operational refinements. In general, the EVP system was evaluated as an effective and highly practical tool that improves emergency-vehicle mobility, arrival-time stability, and operational reliability across diverse dispatch conditions. The combined quantitative and qualitative verification in this study underscores its value as a field-proven technology. Future studies should expand to multiregional longitudinal datasets, controlled analyses considering external variables such as traffic volume and weather, and quantitative evaluation of safety-related impacts such as reductions in intersection collisions or on-route risk exposure to assess the system’s broader policy and operational benefits more comprehensively.

본 연구는 도심 차량 방호용 볼라드의 기초 치수와 형상이 충돌 성능에 미치는 영향을 평가하였다. 1,500 kg 승용차 30 km/h 의 속도로 정면충돌 시험에서 현행 200-200-250 mm 독립기초는 전도 및 이탈이 발생했고 차량 감속은 미미하였다. 이를 바탕으로 LS-DYNA 모델을 검증하고, 정사각 기초의 치수(200–700) 및 동일 면적 원형과 정사각형 기초 비교해석을 수행하였다. 결과적으로 기초의 치수가 커질수록 감속률이 증가했으며 700-700-250의 기초에서 60%의 감속(잔류 12 km/h)이 확인되었다. 동일 면적 비교에 서 정사각형 기초가 원형 기초보다 우수하였고, 이는 측면 접촉면 증가와 회전 저항 증대에 기인한다. 현행 국내 볼라드는 기존 관행만으 로 요구되는 성능을 충족하기 어려운 실정이다. 본 연구는 국내 도심 조건에서 볼라드 독립기초의 치수와 형상에 따른 차량 감속 특성을 정량적으로 제시하였으며, 향후 볼라드 기초 설계 기준 및 방호 성능 평가 체계를 정립하는 데 활용가능한 기초자료를 제공한다.

운전 시뮬레이션을 이용하여 3-수준 자율주행 상황을 구현한 후 청년 및 고령운전자가 주간/야간 운전 조건과 비 운전과제(nonm-driving task: NDT) 수행 여부에 따라 보이는 제어권 인수시간(takeover time: TOT), 차량제어 (vehicle control :VC) 및 주관적 작업부하(subjective workload: SW) 수준에서의 차이를 비교하였다. 실험참가자들에 게는 자율주행 중 NDT를 수행하도록 하였고 NDT 수행 도중 제어권 인수가 요청되면 제어권을 빠르고 정확하게 인수받아 수동운전으로 전방의 장애물을 회피하도록 하였다. 본 연구 결과를 요약하면 다음과 같다. 첫째, 야간 운전 조건과 NDT 수행 조건에서 실험참가자들의 TOT는 증가하였고, 차량에 대한 종적 및 횡적수행 모두 저하되었으며, SW 수준은 더 높았다. 둘째, 청년운전자 집단에 비해 고령운전자들의 VC 수행이 상대적으로 더 저조하였다. 셋째, 고령운전자들은 야간 운전과 NDT 수행 요구가 결합되면 모든 종속측정치에서 청년운전자들에 비해 상대적으로 더 저하된 수행을 보였다. 이러한 결과는 야간 자율주행에서 고령운전자의 주의가 분산될 경우 자율주행 차량과의 상호 작용 및 긴급한 상황에서의 장애물 회피에서 어려움이 증가할 수 있다는 것을 시사한다.

The accelerator pedal of a KLTV was applied in the form of a carryover utilizing the products of a civilian vehicle. There was case in which it was damaged because it did not reflect the military's specificity, Therefore the material and shape of the accelerator pedal were improved to confirm the strength improvement effect of about 86%, It can prevent accidents and contribute to securing mobility by presenting and applying fracture strength standards suitable for the military operation environment.

To improve vibration reduction in the railway vehicle, the semi-active suspension system using MR damper was developed and the vibration performance of the passive suspension system and a semi-active MR suspension system was compared. For the experiment, the MR damper and suspension system were designed and manufactured. Tensile and compression tests were performed on the MR damper while varying the input current. The damping force of the MR damper was measured and analyzed using the Bingham model. The railway vehicle was modeled with 9 degrees of freedom, and the sky hook control algorithm was simulated using the MR damper, using the Bingham model. This verified the effectiveness of the sky hook controller. Furthermore, to compare the vibration performance of the railway vehicle, the driving test was conducted with the MR damper and the passive damper. The lateral acceleration vibration reduction performance of the suspension system with MR dampers and passive dampers was verified, and it was confirmed that the vibration reduction performance of the vehicle with the semi-active suspension system using MR damper was approximately 50% better than that of the vehicle with the passive damper.

In this study, we investigated and analyzed the impact of changes in driving speed and inter-vehicle distance on users’ perceived tension during autonomous vehicle operation. To this end, a survey experiment was conducted for both urban roads and highways. The results show that the greatest changes in perceived tension occurred in the range of 50–70 Km/h and 50–70 m following distance on urban roads, and in the range of 80–100 Km/he and 60–80 m following distance on highways. Furthermore, modeling user behavioral responses to perceived tension based on changes in speed and following distance revealed that linear models best described the relationship for speed on both urban roads and highways. For the following distance, a quadratic model was the most suitable for urban roads, whereas a logarithmic model best fit the highway data. These findings are expected to contribute to practical operational guidelines for autonomous vehicles by alleviating users’ psychological discomfort and enhancing public acceptance. Future research will extend this study using a driving simulator to examine user responses in more realistic driving environments.

Autonomous vehicles are widely expected to be commercialized in the near future. This would naturally lead to situations in which existing vehicles and autonomous vehicles would be on the road at the same time, which would pose a notable hazard to traffic safety. From this perspective, high-risk factors relating to this deployment should be identified to prepare measures to promote traffic safety. However, at this point, deriving high-risk factors based on actual data is problematic because autonomous vehicles have not yet been widely commercialized. In this study, we derive high-risk factors that would apply if autonomous vehicles were allowed to drive alongside vehicles driven by humans using a meta-analysis. We synthesized factors related to autonomous vehicles mentioned in the relevant literature. An analysis was conducted based on a total of 58 documents according to five keywords related to autonomous vehicles (crash factors, scenarios, predictive models, laws, and regulations). We also performed a binary meta-analysis of factors related to autonomous vehicles according to these keywords and a meta-analysis of effect size according to the relative size of factors to evaluate them comprehensively. We found that many different aspects of driving such as navigating intersections, lanes, fog, rain, acceleration and deceleration, rear-end collisions, inter-vehicle spacing, and pedestrian collisions were notable as high-risk factors. This study provides basic data to identify high-risk factors to support the development of related prediction models.

The center bearing of the propeller shaft in the KM-Sam mounted vehicle is a component that requires high durability due to high-speed rotation and it must exhibit strong resistance to vibration and strees. However some Republic of Korea Air Force (ROKAF) units have experienced failures where the center bearing bracket breaks, leading th the detachment of the propeller shaft assembly. This issue has only occurred with domestically developed center bearings, A root cause analysis confirmed excessive second-order components and stress, Therefore improved results were derived through comparative testing with imported parts, and the effectivenss was verified by applying them to actual vehicles.

Overloaded and improperly loaded trucks cause serious road hazards, such as rollovers and cargo falls. Although automatic enforcement methods are being studied, they face challenges in accuracy and legal application. Thus, a technology for direct tracking and enforcement is needed. This study uses EfficientNet to extract features of vehicles and license plates, and applies cosine similarity to identify the same vehicle. Comparisons were divided into “same vehicle” and “similar vehicle,” with a threshold-based method and five classification types. Results showed that the average similarity of the same vehicle group was 0.11 higher than that of the similar vehicle group. The accuracy of correctly identifying the same vehicle was 84.54%. Integrating OCR or LPR is expected to further improve tracking performance.