• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.27-37
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• 2012

Even thought the firefighters have to hurry to the scene to extinguish the blaze, the fire engines could not rushed out due to the worst of traffic condition. Traffic signal control is one of the most important methods to minimize the fire engines's travel time. The focus of this paper is to develop a traffic control strategy, which is emergency vehicle preemption algorithm considering pedestrian in order to reduce travel time of emergency vehicle. This algorithm also includes recovering strategy after preemption signal to minimize the other vehicle's delay. In order to estimate the effectiveness of traffic control, traffic simulation was performed using VISSIM micro simulation tool for two different kinds of networks, which were non-coordinated corridor and coordinated corridor. The differences of travel time and average delay between emergency vehicle and ordinary vehicle were respectively estimated under pre-existed pretimed signal and preemption traffic control at two respective networks. The results of the simulation for the emergency vehicle, travel time was reduced to 36.8~43.3% under "Add or Subtract" method whereas it was reduced to 30.7~46.0% under "Dwell" method. In addition, in non-coordinated corridor case of ordinary vehicle, average control delay of "Dwell" method was increased 33.5% whereas it grew 0.5% under coordinated corridor. And "Add or Subtract" method was confirmed that average control delay of ordinary vehicle was increased 0.7% under non-coordinated corridor whereas it swelled 4.5% under coordinated corridor.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.41-47
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• 2013

PURPOSES : The purpose of this study is about noise which is generated from roads and is consist of irregular frequency variation from low frequency to various band. The existing methods of noise reduction are sound barrier that uses insulation material and absorbing material or have applied passive technology of noise reduction by devices. The total frequency band is needed to apply active noise control. METHODS : In this study applies to the field of road traffic environment, signal processing controller and various analog signal input/output, the amplifier module is based on parallel-core embedded processor designed. DSP performs the control algorithm of the road traffic noise. Noise sources in the open space performance of evaluation were applied. In this study, controller of active signal processor was designed based on the module of audio input/output and main controller of embedded process. The controller of active signal processor operates noise reduction algorithm and performance tests of noise reduction in inside and outside environment were executed. RESULTS : The signal processing controller with OMAP-L137 parallel-core processors as the center, DSP processors in the active control operations dealt with quickly. To maximize the operation speed of an object and ARM processor is external function keys and display for functions and evaluating the performance management system was designed for the purpose of the interface. Therefore the reduction of road traffic noise has established an electronic controller-based noise reduction. CONCLUSIONS : It is shown that noise reduction is effective in the case of pour tonal sound and complex tonal sound below 500Hz by appling to Fx-LMS.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1122-1129
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• 2015

This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.1-16
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• 2011

With the increasing number of vehicles in use in our daily life and the rise of traffic congestion problems, many methods and models have been developed for real time optimisation of traffic lights. Nevertheless, most methods which consider real time physical queue sizes of vehicles waiting for green lights overestimate the optimal cycle length for such real traffic control. This paper deals with the development of a generic hybrid model describing both physical traffic flows and control of signalised intersections. The firing times assigned to the transitions of the control part are considered dynamic and are calculated by a simplified optimisation method. This method is based on splitting green times proportionally to the predicted queue sizes through input links for each new cycle time. The proposed model can be easily translated into a control code for implementation in a real time control system.

• Journal of Applied Reliability
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• v.10 no.4
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• pp.265-278
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• 2010

Module of the LED traffic signal is the core component for the care of driver and walker. Also it is important one to control the traffic. If it is against the criteria of brightness, it is the source of the people's death and traffic congestion. Therefore, it is a list of articles desired the security of stability. However, there is not the analysis of failure and not preserve the uniformity of quality. Therefore, it is necessary to establish the criteria of appreciation for the module of the LED traffic signal to analysis the data of failure. In this paper, we investigate the performance test, environment field test and test of reliability appreciation to improve the reliability. We also set up the criteria of success decision using the real measurement data.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.195-209
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• 2024

The current road traffic signal controller developed in the 1990s has limitations in flexibility and scalability due to power supply problems, various communication methods, and hierarchical black box structures for various equipment and devices installed to improve traffic safety for road users and autonomous cooperative driving. In this paper, we designed a road traffic safety facilities equipment and devices integrated management system that can cope with the rapidly changing future traffic environment by solving the using direct current(DC) and power supply problem through the power over ethernet(PoE) technology and centralized data-driven control through message broker technology. In addition, a data-driven real-time control method for road traffic safety facilities equipment and devices operating based on time series data was implemented and verified.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.91-93
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• 2009

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.907-910
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• 1993

This paper describes the use of fuzzy control and decision making to simulate the control of traffic flow at an intersection. To show the value of fuzzy logic as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller, a computer simulation was constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment, and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. In the hardware verifications, fuzzy logic was used to control acceleration of a model train on a circular path. For the software experiment, the fuzzy logic controller proved better than conventional control methods, especially in the case of highly uneven traffic flow between different directions. On the hardware si e of the research, the fuzzy acceleration control system showed a marked improvement in smoothness of ride over crisp control.