일반차량과 자율주행차량이 혼재하는 상황에서 발생가능한 미래 재난상황에 대한 관리방안 준비가 필요하다. 특히 재난 상황 중 안 개 발생 시 시야 확보가 어려운 일반차량 운전자와 센서기반 자율주행차량의 주행 특성이 다를 수 있다. 해당 상황에서의 문제점을 도출하고 이를 극복하기 위해 혼합교통류 관리 방안을 제안하고자 한다. 본 연구에서는 다양한 재난 상황 중 안개를 연구 대상으로 설정하였다. 과거 기상 상황별 일반차량을 주행 특성을 이력자료로 분석한 후, 안전한 교통흐름을 유지하기 위하여 자율주행차에게 정 보를 제공하는 방안을 제안한다.

도로 위 노면전차 트램를 포함한 다양한 이동수단 흐름을 원활하게 유지하기 위해서는 효율적인 교통 신호 제어가 필요하다. 검증 되지 않은 기술의 현장 평가는 교통안전 측면에서 위험하기에 대부분 가상환경을 통해 적용 기술검증을 선행한다. 본 연구는 다양한 교통신호 제어 알고리즘을 센터 수준에서 적용하는 가상 실험환경 마련을 위한 기능적 요구사항을 정의한다. 기능적 요구사항으로 가 상환경 센터 기반으로 실험을 시작하거나 중지하는 기능, 교통량 등 입력값을 입력하는 기능 등의 기본적 요구사항을 도출하였다. 이 렇게 정의된 기능적 요구사항은 향후 트램 등 다양한 교통수단을 대상으로 하는 가상환경 센터 구축 과정에 효율적으로 참조될 수 있 을 것으로 기대된다.

기존 신호제어기법은 과거 주기에 파악된 교통상황을 바탕으로 다음 주기의 교통신호시간을 설계하는 방식으로 신호시간을 설계하기 위해 관측할 때의 교통상황과 신호시간을 제공받는 교통상황 간의 간극이 존재하였다. 또한, 설정된 주기길이 동안 차량이 교차로에 일정하게 도착하는 균일분포를 가정하지만, 실제 교차로에 도착하는 교통량의 행태는 비 균일분포로 실제 교통수요에 대응하기 어렵 다는 한계가 존재한다. 본 연구는 이러한 한계를 극복하기 위해 교차로로 진입하는 상류 교차로의 교통정보를 활용하여 단기 미래 도 착 교통량 예측모델 개발을 통해 관측 시점과 제공 시점 간의 간극을 최소화한다. 또한, 기존 주기길이 동안의 교통량 도착분포를 비 균일분포로 가정하여 주기길이가 고정되지 않는 방식(Acyclic)의 적응식 신호제어 기법(ATC) 개발한다. 제안된 단기 미래 도착 교통 량 예측모델은 실제 스마트교차로 자료를 가공하여 시뮬레이션을 통하여 학습데이터를 구축하여 장단기 메모리(LSTM) 모형과 시간 분산(TimeDistributed) 모형을 적용하여 딥러닝 모델을 개발하였다. 적응식 교통신호제어 기법은 실시간 예측 교통량을 활용하여 교통 류별 예측 지체 산출을 통하여 지체가 최소화되는 현시 종료 지점에서 현시를 종료하고 다음 시간 단계에서 예측된 교통량을 통해 최 적 현시를 재산출하는 롤링 호라이즌(Rolling Horizon)을 수행한다. 제안 신호제어 기법의 평가를 위해 미시적 교통 시뮬레이션을 활 용하여 기존 신호제어 기법인 TOD 신호제어 기법과 제안기법 간의 평가를 수행하였다.

High-rise buildings are equipped with TMD (Tuned Mass Damper), a vibration control device that ensure the stability and usability of the building. In this study, the seismic response control performance was evaluated by selecting the design variables of the TMD based on the installation location of the twisted irregular building. To this end, we selected analysis models of 60, 80, and 100 floors with a twist angle of 1 degree per floor, and performed time history analysis by applying historical seismic loads and resonant harmonic loads. The total mass ratio of TMDs was set to 1.0%, and the distributed installation locations of TMDs were selected through mode analysis. The analysis results showed that the top-floor displacement responses of all analysis models increased, but the maximum story drift ratio decreased. In order to secure the seismic response control performance by distributed installation of TMDs in twisted irregular buildings, it is judged that the mass ratio distribution of TMDs will act as a key variable.

With the growth of silicon-based semiconductor sensors in the global sensor market, advancements in body motion detection for wearable devices and sustainable health monitoring have accelerated. This has led to a significant attention on various sensors with excellent flexibility and stretchability, such as PDMS, in numerous applications. In this study to adjust the sensitivity of conventional conductive pressure sensors, a porous sponge structure was initially created using a sugar template method. The polymer was prepared with four different ratios (5:1, 10:1, 20:1, 30:1) to achieve varying flexibilities. To ensure conductivity, the sponge was coated using a dip-coating method with a 3wt% CNT solution. The conductive sponges with various ratios were tested for sensitivity, demonstrating characteristics suitable for a wide range of pressure sensing applications.

In the present study, the inertial electromagnetic actuator (IEA) and the FxLMS (filtered-x least mean square) method were applied to study vibration control using the active mount. IEA was designed and manufactured for the experiment, and FxLMS algorithm was developed to evaluate control performance and mount dynamic characteristics. For the vibration control experiment, active mounts were installed at the top and bottom, and the lower active mount controls the force transmitted to the structure by the excitation signal from the upper active mount. The experiment was performed by simultaneously exciting three frequencies in three axes. From the experimental results, it was confirmed that the force measured at the lower active mount when the actuator is off is greatly reduced when the actuator is on, and that vibration reduction in the vertical z-axis is more effective than vibration reduction in the x-y plane.

This paper aims to study the modeling and controller of an electrically driven tractor optimized for energy efficiency under off-road conditions and when subjected to loads such as plowing. The dynamic model design is aimed at a 30kW electric tractor. The vehicle model consists of a 30kW motor, transmission, wheels, and a controller, designed using the commercial software Matlab/Simulink. In order to optimize energy efficiency under load conditions, this paper designs and implements a PID controller focusing on the vehicle's speed and wheel slip. The newly proposed electric tractor modeling and PID controller aim to demonstrate improved energy efficiency through simulation.

The purpose of this review is to provide a comprehensive analysis of the intricate relationships between cognitive control, depression, and emotion regulation. Cognitive control, encompassing processes such as attentional control, inhibitory control, and cognitive flexibility, plays a central role in regulating thoughts, behaviors, and emotions in alignment with internal goals and external demands. Depression, characterized by persistent feelings of sadness, hopelessness, and cognitive impairments, is associated with deficits in cognitive control processes. Emotion regulation strategies, such as cognitive reappraisal and expressive suppression, enable individuals to modulate emotional experiences and responses. The bidirectional relationships between cognitive control, depression, and emotion regulation underscore the complexity of cognitive and emotional processes in depression. Understanding these relationships is crucial for developing targeted interventions aimed at promoting cognitive and emotional well-being and preventing depression onset and recurrence. Moreover, recognizing the roles of cognitive control and emotion regulation in depression holds promise for informing clinical practice and enhancing therapeutic interventions. This review highlights the importance of considering cognitive control and emotion regulation in the assessment and treatment of depression and provides insights for future research and clinical practice.

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.

스마트팜으로 알려진 지능형 온실환경 제어(스마트제어)가 겨울철 장미 ‘비스트’의 절화품질에 미치는 영향을 기존의 농 가 수동제어(수동제어)와 비교하여 조사하였다. 그 결과 지능 형 스마트제어가 온실환경인 기온, 배지온도, 상대습도를 겨 울철 절화 장미 생산에 적합하게 유지시켰다. 반면, 수동제어 는 적정한 환기와 상대습도 관리에 다소 불리하였고, 결과적 으로 겨울철 과습으로 흔히 발생하는 잿빛곰팡이 발병이 증가 했으며 절화수명이 단축되었다. 절화의 생체량, 길이, 수명 등 절화품질 역시 스마트제어를 통해 상대적으로 개선되었다. 이 번 연구를 통해 스마트제어 방식이 시설환경관리 측면에서 겨 울철 고품질 절화 장미 생산에 유리하다는 것을 확인하였다.

PURPOSES : This study develops a model that can estimate travel speed of each movement flow using deep-learning-based probe vehicles at urban intersections. METHODS : Current technologies cannot determine average travel speeds for all vehicles passing through a specific real-world area under obseravation. A virtual simulation environment was established to collect information on all vehicles. A model estimate turning speeds was developed by deep learning using probe vehicles sampled during information processing time. The speed estimation model was divided into straight and left-turn models, developed as fully-offset, non-offset, and integrated models. RESULTS : For fully-offset models, speed estimation for both straight and left-turn models achieved MAPE within 10%. For non-offset models, straight models using data drawn from four or more probe vehicles achieved a MAPE of less than 15%. The MAPE for left turns was approximately 20%. CONCLUSIONS : Using probe-vehicle data(PVD), a deep learning model was developed to estimate speeds each movement flow. This, confirmed the viability of real-time signal control information processing using a small number of probe vehicles.