• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.45-58
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• 1996

In a large signal intersection, it is the most important to set phase sequences and phase intervals of traffic signal in order to improve the efficiency of the capacity as well as safety. These setting allows to select the best sequence of signal phase among several alternatives, and thus to rearrange the starting and ending points of the individual phase using an effective interphase periods (EIP). The EIP is a gap between previous and current traffic movements at a potential collision point in an intersection. Each of traffic movements has an equality for safety and efficiency at the balanced condition of EIP. This paper presents how to set optimally the phase sequences and intervals of traffic signal in an intersection using phase based approach. And in the second part, we applied the theory developed in the first part. In particular, a numerical example of phase base signal setting is presented using a matrix computation method in order to select the best sequence among several alternatives, and thus to rearrange the starting and ending points of the individual phase using the EIP. This method also allows to apply to optimum signal setting even in five-lag or staggered-type intersection.

• Journal of Korean Institute of Industrial Engineers
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• v.3 no.1
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• pp.49-53
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• 1977

The coordinated control of the traffic signals of adjacent intersections can reduce delays, relative number of stops and congestions in the coordinated traffic area. The road capacity can be increased to a certain extend because the stopping and starting of vehicles facing red traffic lights can be avoided in many instances due to the progression established along an artery. However, if traffic centers or leaves the main flow in irregular volumes on the intermediate road section, a coordination of traffic signals is unnecessary and may even be harmful. Therefore, a computer simulation model to simulate and predict the effectiveness of a synchronized traffic signal system in the CBD of Seoul was developed and alternative policy variables, such as cycle time, offsets, phase splits, to be fed into the simulation model had to be generated. This is a report of (1) the development of a heuristic algorithm for the determination of phase splits when there are amber periods specifically reserved for left turns and (2) the computerization of time-space diagramming.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.119-121
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• 2022

In this paper, we will make a model that finds optimal phase for each crossroad. When the traffic volume, traffic capacity, and the lane width of every direction is given for each crossroad, we aim to find the most efficient phase. We established an evaluation function that evaluates the efficiency of each phase using the values of the average waiting time in one direction, the average delay time, the standard deviation of the delay time, and the average delay time in each direction. The time allocation to optimize a phase pattern can be obtained by using the gradient decent method. Through this research, we hope to decrease the waiting time in transporation, thus improving the overall traffic condition in cities.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.117-133
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• 1996

In the paper a superior performance algorithm compared to the existing vehicle actuated controller and time fixed controller and the additional controller is described through realization of fuzzy traffic phase controller. Fuzzy theory is encouraging since the application is similar to human's decision ability that is approately coped with uncertain conditions. The paper presents that selection of the phase adequated the variable traffic conditions through the fuzzy theory algorithm and decision of optimal cycle time approated the uncertain traffic volume are predominant in traffic jam solution compared to the existing Webster's cycle time decision method and the sequential traffic phase design method and dual-ring phase operation system.

• Environmental Engineering Research
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• v.22 no.1
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• pp.19-30
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• 2017

Direct catalysis of vapors from vacuum pyrolysis of biomass was performed on MCM-41 to investigate the effects of operating parameters including catalyzing temperature, catalyzing bed height and system pressure on the organic yields. Optimization of organic phase yield was further conducted by employing response surface methodology. The statistical analysis showed that operating parameters have significant effects on the organic phase yield. The organic phase yield first increases and then decreases as catalyzing temperature and catalyzing bed height increase, and decreases as system pressure increases. The optimal conditions for the maximum organic phase yield were obtained at catalyzing temperature of $502.7^{\circ}C$, catalyzing bed height of 2.74 cm and system pressure of 6.83 kPa, the organic phase yield amounts to 15.84% which is quite close to the predicted value 16.19%. The H/C, O/C molar ratios (dry basis), density, pH value, kinematic viscosity and high heat value of the organic phase obtained at optimal conditions were 1.287, 0.174, $0.98g/cm^3$, 5.12, $5.87mm^2/s$ and 33.08 MJ/kg, respectively. Organic product compositions were examined using gas chromatography/mass spectrometry and the analysis showed that the content of oxygenated aromatics in organic phase had decreased and hydrocarbons had increased, and the hydrocarbons in organic phase were mainly aliphatic hydrocarbons. Besides, thermo-gravimetric analysis of the MCM-41 zeolite was conducted within air atmosphere and the results showed that when the catalyst continuously works over 100 min, the index of physicochemical properties of bio-oil decreases gradually from 1.15 to 0.45, suggesting that the refined bio-oil significantly deteriorates. Meanwhile, the coke deposition of catalyst increases from 4.97% to 14.81%, which suggests that the catalytic activity significantly decreases till the catalyst completely looses its activity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.48-54
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• 2023

Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.29-37
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• 2017

Intersection signal's phase time is calculated and determined by car and pedestrian traffic volume. If signal phase time and traffic volume dis-matched, cars and pedestrians have much delay time. This paper suggested an All-Red phase application method that cars and pedestrians securing safety and minimizing traffic signal waiting time. The key solution of this suggested method is determining All-Red phase operation by using sum of spare green time that have no passing cars. That is, total time of spare green time that have no passing cars is longer than All-Red phase time, operating All-Red phase has an effect. And case study carried out at the signalized intersection, revealed that this suggested method has much effectiveness.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.2 s.10
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• pp.61-71
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• 2006

The main purpose of this study is to search a method for reducing traffic accident at signalized intersections. One of the important factors for this is the Left-turn phase sequence. In 1985, the operational principle of Left-turn phase Sequence was changed from Lagging left-turn to Leading left-turn in Korea. Then there was a resonable motive-no exclusive left turn-lane and narrow intersection. So, it is necessary to evaluate the performance difference between Leading and Lagging left -turn phase Sequence. The process of this study is as follows: $\cdot$ First, all the intersection was divided three parts for analysis the traffic safety: Inside part of an Intersection, Crosswalk, Intersection approach and exit. $\cdot$ Second, a safety analysis was performed by using the concepts of 'Effective interphase Period(EIP)' and 'Conflict method' The Study result is that the benefit of of phase Sequence changes from Leading to Lagging phase were significant. For an example the Accident cost will reduced about 41.8 billion won per year in korea.

• Wind and Structures
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• v.27 no.4
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• pp.255-267
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• 2018

This paper investigated the wind-snow flow around the bogie region of a high-speed train under crosswinds using a coupled numerical method of the unsteady Realizable $k-{\varepsilon}$ turbulence model and discrete phase model (DPM). The flow features around the bogie region were discussed and the influence of bogie fairing height on the snow accumulation on the bogie was also analyzed. Here the high-speed train was running at a speed of 200 km/h in a natural environment with the crosswind speed of 15 m/s. The mesh resolution and methodology for CFD analysis were validated against wind tunnel experiments. The results show that large negative pressure occurs locally on the bottom of wheels, electric motors, gear covers, while the positive pressure occurs locally on those windward surfaces. The airflow travels through the complex bogie and flows towards the rear bogie plate, causing a backflow in the upper space of the bogie region. The snow particles mainly accumulate on the wheels, electric motors, windward sides of gear covers, side fairings and back plate of the bogie. Longer side fairings increase the snow accumulation on the bogie, especially on the back plate, side fairings and brake clamps. However, the fairing height shows little impact on snow accumulation on the upper region of the bogie. Compared to short side fairings, a full length side fairing model contributes to more than two times of snow accumulation on the brake clamps, and more than 20% on the whole bogie.