PURPOSES : In this study, the existence of an optimal pattern among transition methods applied during changes in traffic signal timing was investigated. We aimed to develop this pattern into an artificial intelligence reinforcement-learning model to assess its effectiveness METHODS : By developing various traffic signal transition scenarios and considering 19 different traffic signal transition situations that can be applied to these scenarios, a simulation analysis was performed to identify patterns through statistical analysis. Subsequently, a reinforcement-learning model was developed to select an optimal transition time model suitable for various traffic conditions. This model was then tested by simulating a virtual experimental center environment and conducting performance comparison evaluations on a daily basis. RESULTS : The results indicated that when the change in the traffic signal cycle length was less than 50% in the negative direction, the subtraction method was efficient. In cases where the transition was less than 15% in the positive direction, the proposed center method for traffic signal transition was found to be advantageous. By applying the proposed optimal transition model selection, we observed that the transition time decreased by approximately 70%. CONCLUSIONS : The findings of this study provide guidance for the next level of traffic signal transitions. The importance of traffic signal transition will increase in future AI-based traffic signal control methods, requiring ongoing research in this field.

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.

PURPOSES : This study presents a general guideline for the initial management of traffic signal timings in response to traffic incidents, prior to the implementation of specific treatments in detail. The proposed solution includes a set of optimal reductions in the green time rates at three signalized intersections upstream. METHODS : To account for the various traffic and incident conditions that may be encountered, a total of 36 traffic-condition scenarios were prepared. These scenarios encompass a wide range of conditions, from unsaturated to near-saturated conditions, and were designed to provide a comprehensive understanding of the impact of traffic conditions on signal timing. For each of the traffic conditions, all 27 traffic signal timing combinations were subjected to testing. A total of 972 simulation analyses were conducted using the SUMO model. The results indicated that the scenario with the lowest control delay was the optimal choice. RESULTS : The results indicated that the most effective initial management for the traffic incident would be to reduce the green signal timings by 20% at the first two upstream intersections and by 40% at the third intersection. CONCLUSIONS : We propose reducing the green times by 20% at the first and second intersections and by 40% at the third intersection as the initial response of the traffic signal control center when a traffic incident occurs.

In this study, we investigated the time signal devices of Deungnu (circa 1270) and Gungnu (1354), the water clocks produced during the Yuan Dynasty (1271–1368). These clocks influenced Heumgyeonggaknu (1438) of the Joseon Dynasty (1392–1910), exemplifying the automatic water clocks of the Yuan Dynasty. Deungnu, Gungnu, and Heumgyeonggaknu can be considered as automatic mechanical clocks capable of performances. The Jega-Yeoksang-Jip (Collection of Calendrical and Astronomical Theories of Various Chinese Masters) contains records of Deungnu extracted from the History of the Yuan Dynasty. We interpreted these records and analyzed reproduction models and technical data previously produced in China. The time signal device of Deungnu featured a four-story structure, with the top floor displaying the four divine constellations, the third floor showcasing models of these divinities, the second floor holding 12-h jacks and a 100-Mark ring, and the first floor with four musicians and a 100-Mark Time-Signal Puppet providing a variety of visual attractions. We developed a 3D model of Deungnu, proposing two possible mechanical devices to ensure that the Time-Signal Puppet simultaneously pointed to the 100-Mark graduations in the east, west, south, and north windows: one model reduced the rotation ratio of the 100-Mark ring to 1/4, whereas the other model maintained the rotation ratio using four separate 100-Mark rings. The power system of Deungnu was influenced by Suunuisangdae (the water-driven astronomical clock tower) of the Northern Song Dynasty (960–1127); this method was also applied to Heumgyeonggaknu in the Joseon Dynasty. In conclusion, these automatic water clocks of East Asia from the 13th to 15th centuries symbolized creativity and excellence, representing scientific devices that were the epitome of clock-making technology in their times.

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.

During PIV (Physical Inventory Verification), the IAEA has been inspecting the CANDU-Type spent fuels using an optical fiber-based scintillation detector. KINAC has developed a new verification instrument to deal with problems of the existing one such as low sensitivity, heavy and large dimension, and inconvenience-in-use. Our previous studies focused on how to develop the new instrument and had not included its performance tests. Field tests were carried out recently at Wolsung unit 4 to evaluate performance of the existing and new instruments. The objective of this paper is to discuss background noise produced in the optical fiber signal cable itself. The verification equipment for the CANDU-type Heavy Water Reactor spent fuels uses a scintillation detector to bond a scintillation material to the end of an optical signal cable. At this time, the radiation signal obtained by a data acquisition system is the signal generated from the scintillator (p-terphenyl organic scintillator) and the optical signal cable ; The signal produced in the optical cable itself is background noise to degrade the spent fuel verification equipment. To characterize the background radiation noise, the spent fuel bundles at Wolsung Unit 4 were measured using the optical fiber cable without the radiation scintillator. This signal is generated by reaction of the optical cable and the radiation emitted from the spent fuel. From experimental results, it was observed that the background noise signal of the optical cable increased as the optical cable went down in the downward direction, because the cable length irradiated by the radiation increased with the optical cable area in the spent fuel storage pool. Difference in the background noise signal was dependent on the location of the vertical direction and the signal of the new optical cable was up to about 5 times higher than that of the existing cable. While, the new cable has the cross-section area about 3.2 times larger than the old cable. Our past studies showed that total signal amplitude – sum of signals generated from the scintillator and optical fiber - of the new verification instrument was at least about 15 times greater than that of the existing one. Considering the total signal and background noise signal, from this measured results, it was confirmed that the scintillator characteristics – in particular, light output and decay time – has a dominant impact on the signal sensitivity of the newly developed instrument. More details will be discussed at the conference.

This study analyzes the seismic response of traffic light poles, considering soil-foundation effects through nonlinear static and time history analyses. Two poles are investigated, uni-directional and bi-directional, each with 9 m mast arms. Finite element models incorporate the poles, soil, and concrete foundations for analysis. Results show that the initial stiffness of the traffic light poles decreases by approximately 38% due to soil effects, and the drift ratio at which their nonlinear behavior occurs is 77% of scenarios without considering soil effects. The maximum acceleration response increases by about 82% for uni-directional poles and 73% for bi-directional poles, while displacement response increases by approximately 10% for uni-directional and 16% for bi-directional poles when considering soil-foundation effects. Additionally, increasing ground motion intensity reduces soil restraints, making significant rotational displacement the dominant response mechanism over flexural displacement for the traffic light poles. These findings underscore the importance of considering soil-foundation interactions in analyzing the seismic behavior of traffic light poles and provide valuable insights to enhance their seismic resilience and safety.

Tomatoes in greenhouse are a widely cultivated horticultural crop worldwide, accounting for high production and production value. When greenhouse ventilation is minimized during low temperature periods, CO2 enrichment is often used to increase tomato photosynthetic rate and yield. Plant-induced electrical signal (PIES) can be used as a technology to monitor changes in the biological response of crops due to environmental changes by using the principle of measuring the resistance value, or impedance, within the crop. This study was conducted to investigate the relationship between tomato growth data, vital response, and PIES resulting from CO2 enrichment in greenhouse tomatoes. The growth of tomato treated with CO2 enrichment in the morning was significantly better in all items except stem diameter compared to the control, and PIES values were also higher. The growth of tomato continuously applied with CO2 was better in the treatment groups than control, and there was no significant difference in chlorophyll fluorescence and photosynthesis. However, PIES and SPAD values were higher in the CO2 treatment group than control. CO2 enrichment have a direct relationship with PIES, growth increased, and transpiration increased due to the increased leaf area, resulting in increased water absorption, which appears to be reflected in PIES, which measures vascular impedance. Through this, this study suggests that PIES can be used to monitor crops due to environmental changes, and that PIES is a useful method for non-destructively and continuously monitoring changes of crops.

In this paper, the EMP-related standards and test methods used by the civilian and military have been introduced. The incoming EMP signal for seven military RF antennas which are the first to face EMP threats among military weapon systems have been also measured and analyzed. Overall, as the applied signal strength increased, the strength of the EMP signal entering in the antenna also showed an upward trend. The highest level of entering was observed at the peak value of the applied EMP signal, 50 kV/m. And at the peak value, all antennas received threatening signals. In particular, antennas in low frequency bands such as AM and FM were getting high voltage signals as high as thousands of volts. This means that the weapon systems linked to the antennas could suffer severe damage. Therefore, based on this paper, systematic research for EMP threat should be conducted to identify EMP vulnerabilities of major weapons systems and to devise practical protective measures.

PURPOSES : This paper proposes an artificial neural network (ANN)-based real-time traffic signal time design model using real-time field data available at intersections equipped with smart intersections. The proposed model generates suitable traffic signal timings for the next cycle, which are assumed to be near the optimal values based on a set of counted directional real-time traffic volumes. METHODS : A training dataset of optimal traffic signal timing data was prepared through the CORSIM Optimal Signal Timing program developed for this study to find the best signal timings, minimizing intersection control delays estimated with CORSIM and a heuristic searching method. The proposed traffic signal timing design model was developed using a training dataset and an ANN learning process. To determine the difference between the traditional pre-time model primarily used in practice and the proposed model, a comparison test was conducted with historical data obtained for a month at a specific intersection in Uiwang, Korea. RESULTS : The test results revealed that the proposed method could reduce control delays for most of the day compared to the existing methods, excluding the peak hour periods when control delays were similar. This is because existing methods focus only on peak times in practice. CONCLUSIONS : The results indicate that the proposed method enhances the performance of traffic signal systems because it rapidly provides alternatives for all-day cycle periods. This would also reduce the management cost (repeated field data collection) required to increase the performance to that level. A robust traffic-signal timing design model (e.g., ANN) is required to handle various combinations of directional demands.

PURPOSES : This study aims to develop and validate timing transition techniques for real-time traffic signal operations, departing from conventional methods based on past commuting traffic patterns. METHODS : In this study, we propose two traffic signal transition techniques that can perform transitions while minimizing disruptions within a short period. The Proposed 1 technique involves an unconditional transition within one cycle and allows for the allocation of offset changes to both the coordinated and non-coordinated phases. The Proposed 2 technique performs transitions within 1-2 cycles based on the offset change rate and considers the non-coordinated phase for allocating offset changes. RESULTS : Functional improvements of the proposed techniques were validated. For validation, simulated traffic signal transition scenarios were created, and a comparative analysis of the transition techniques was performed based on the selected analysis approaches. The results showed that the Proposed 1 technique exhibited the lowest delay during the approximated saturated transitions, whereas the Subtract technique showed the lowest delay during the non-saturated transitions. CONCLUSIONS : These findings emphasize the importance of selecting and applying appropriate transition techniques tailored to individual traffic scenarios. The proposed transition techniques provide valuable insights for improving real-time traffic signal operations, and contribute to the overall efficiency and effectiveness of traffic management in highway corridors.

Failure diagnoses on large diesel engine are commonly detected when a deviation or fluctuation in its temperature, pressure, vibration or noise set parameter limits arises. These parameters can be easily monitored and can provide information of the engine’s present state depending on external environment and operating conditions. On the other hand, long term monitoring and condition management can be interfaced into the engine’s existing operating system. The approach is seen to keep track of monitored machines’ status using resonance and vibration amplitude. In particular, these signals will be able to identify complex vibration characteristic pertaining to such as engine torque output and support mounts. In this paper, a basic research for large diesel engine diagnosis was carried-out. The failure diagnosis collects and monitors the vibration state time history by using various vibration signals with reference to ISO 13373-1. Further, this monitoring system in the field of large diesel engines has not been applied practically and the results of this study are presented herein.