• 한국ITS학회지
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• v.1 no.1
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• pp.69-73
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• 2003

A transportation problem is a serious theme to be solved urgently in the motor era of 20 million vehicles. Recently ITS has been introduced to optimize the efficiency of the current roads, because a excess budget and a long term construction are necessary to build new roads. In this paper an outline and major systems of ITS for Ulsan metropolitan city are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.90-98
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• 2015

In this paper, an advanced teaching-learning based optimization(TLBO) method for the magnetic levitation controller of Maglev transportation system is proposed to optimize the control performances. An attraction-type levitation system is intrinsically unstable and requires a delicate control. It is difficult to completely satisfy the desired performance through the methods using conventional methods and intelligent optimizations. In the paper, we use TLBO and clonal selection algorithm to choose the optimal control parameters for the magnetic levitation controller. To verify the proposed algorithm, we compare control performances of the proposed method with the genetic algorithm and the particle swarm optimization. The simulation results show that the proposed method is more effective than conventional methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.60-66
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• 2009

The acceleration noise is valuable index to monitor traffic stability. However, the previous study was performed for the acceleration noise of individual vehicle. The consideration of the acceleration noise for vehicle in the network has not been studied yet. This paper proposes a new macroscopic traffic flow monitoring method based on applying network acceleration noise.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.251-257
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• 2003

In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic Intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not consider emergency vehicles for safety escort.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.397-402
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• 1998

PID controller has been used very widely in the industrial applications. But it is difficult tune the PID gains. In this paper, we present a design of optimal 2-DOF PID controller for control of container crane which has to control swing motion and trolley position. For tuning of the 2-DOF PID control gains, we used hybrid evolution program(EP). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high accuracy and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.50-56
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• 2003

In the development of complex software system, it is important to use hierarchical use case model due to the complex scope of development procedure. The use case model is core factor of the OMG (Object Management Group)'s UML (Unified Modeling Language) diagrams. In this paper, we propose a novel method to check syntactic consistency automatically in use case models at the different level of abstraction. This method is a rule-based approach which utilizes actor tree, use case tree and use case description. The proposed method is simulated on ITS (Intelligent Transportation System) architecture for the verification.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• ETRI Journal
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• v.44 no.2
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.343-350
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• 2014

Although companies have to concentrate on effort to save cost to survive competition, transportation costs are taking more portions in total sales costs due to globalization in the modern times. It is the reason why Transportation Management System TMS is getting more important. However, it is practically difficult for the system to fit to all of transportation environments and actually many problems are taking place with the system. Therefore, a new idea is necessary to solve such problems fundamentally rather than temporarily or superficially. To do so, if TRIZ, which is a theory that systematically establishes creative ideas on the basis of patent analysis, is employed, it can bring forth a guideline with some creative principles that can be applicable in drawing out innovative ideas based on conceptual shift. The present study aims to propose a methodology of how TRIZ should be applied to solve the problems that happen in TMS as a whole. Particularly, the study focuses on how to design customized TMS system that can be employed for each of different situations in a creative way.