• International Journal of Automotive Technology
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• v.7 no.2
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• pp.145-154
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• 2006

In the companion paper, the composition and structure of the MATDYMO (Multi-Agent for Traffic Simulation with Vehicle Dynamic Model) were proposed. MATDYMO consists of the road management system, the vehicle motion control system, the driver management system, and the integration control system. Among these systems, the road management system and the integration control system were discussed In the companion paper. In this paper, the vehicle motion control system and the driver management system are discussed. The driver management system constructs the driver agent capable of having different driving styles ranging from slow and careful driving to fast and aggressive driving through the yielding index and passing index. According to these indices, the agents pass or yield their lane for other vehicles; the driver management system constructs the vehicle agents capable of representing the physical vehicle itself. A vehicle agent shows its behavior according to its dynamic characteristics. The vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation is conducted for an interrupted flow model and its results are verified by comparison with the results from a commercial software, TRANSYT-7F. The interrupted flow model simulation is implemented for three cases. The first case analyzes the agents' behaviors in the interrupted flow model and it confirms that the agent's behavior could characterize the diversity of human behavior and vehicle well through every rule and communication frameworks. The second case analyzes the traffic signals changed at different intervals and as the acceleration rate changed. The third case analyzes the effects of the traffic signals and traffic volume. The results of these analyses showed that the change of the traffic state was closely related with the vehicle acceleration rate, traffic volume, and the traffic signal interval between intersections. These simulations confirmed that MATDYMO can represent the real traffic condition of the interrupted flow model. At the current stage of development, MATDYMO shows great promise and has significant implications on future traffic state forecasting research.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.441-446
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• 2003

Earlier efforts on optical access concentrated on the design of PONs for the collection and distribution portion of the access network. The PON architecture is very simple but it requires a MAC protocol for control of upstream traffic. The MAC protocol must support QoS (Quality of Service) administration function by various traffic class, efficient dynamic bandwidth assignment function, CDV (Ceil Delay Variation) minimization function etc. This paper proposes a dynamic bandwidth assignment algorithm of the MAC protocol for a broadband access network using an Ethernet Passive Optical Network supporting various traffic class. We compare our proposed with MDRR algorithm using simulation, and confirmed that our proposed Request-Counter algorithm produces shorter average cell delay.

• Advances in Computational Design
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• v.8 no.1
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• pp.1-12
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• 2023

To consider the effects of the increasing speed of next-generation high-speed trains, the existing traffic safety code for railway bridges needs to be improved. This study suggests a numerical method of evaluating the new effects of this increasing speed on railway bridges. A prestressed concrete (PSC) box bridge with a 40 m span length on the Gyeongbu track sector is selected as a representative example of high-speed railway bridges in Korea. Numerical models considering the inertial mass forces of a 38-degree-of-freedom train and the interaction forces with the bridge as well as track irregularities are presented in detail. The vertical deflections and accelerations of the deck are calculated and compared to find the new effects on the bridge arising with increasing speed under simply and continuously supported boundary conditions. The ratios between the static and dynamic responses are calculated as the dynamic amplification factors (DAFs) under different running speeds to evaluate the traffic safety. The maximum deflection and acceleration caused by the running speed are indicated, and regression equations for predicting these quantities based on the speed are also proposed.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.1-11
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• 2001

This paper considers the scheduling of cell-based handoffs to balance the traffic in a fiber-optic microcelluar system. In the system depending on the order of cell based handoff, periodical balancing of the traffic among microcells can be achieved. The cell based handoff problem is formulated as a dynamic programming and the computational complexity is analyzed. Since the scheduling problem requires real time solution, heuristic algorithms are proposed and the computational results are discussed.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.94-96
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• 2009

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 IEEK Conference
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• 1999.06a
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• pp.737-740
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• 1999

This paper deals with a real time optimization algorithm within real time for DRGS(Dynamic Route Guidance System) and evaluate the algorithm. A pre-developed system offers the optimal route in using only static traffic information. In using real-time traffic information, Dynamic route guidance algorithm is needed. The serious problem in implementing it is processing time increase as nodes increase and then the real time processing is impossible. Thus, in this paper we propose the optimal route algorithm with window mechanism for the real-time processing and then evaluate the algorithms.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.119-129
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• 1994

This paper describes system and its algorithm which can measure traffic flow on the road by using industrial television applied in industry. This algorithm is using the real-time processing of dynamic scenes. The processing algorithm of dynamic scenes is developed and proved its validity by designing VISC (Video Information Sampler and Converter). The accuracy of this algorithm is enhanced by allocating sampling points in cross-direction of the vehicles.

• IE interfaces
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• v.14 no.4
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• pp.374-384
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• 2001

The objective of this paper is to design the dynamic route guidance system(DRGS) and develop a genetic algorithm(GA) for finding the multiple shortest paths in real traffic network. The proposed GA finds a collection of paths between source and destination considering turn-restrictions, U-turn, and P-turn that are genetically evolved until an acceptable solution is reached. This paper also shows the procedure to find the multiple shortest paths in traffic network of Seoul.

• Convergence Security Journal
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• v.11 no.1
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• pp.3-10
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• 2011

This paper proposes DPA(Dynamic Priority Assignment) MAC protocol to improve the traffic QoS on the HFC-CATV(Hybrid Fiber Coax CAble TeleVision) network. In results, DPA MAC protocol is the best performance compare with to IEEE 802.14a MAC in mean request delay, mean access delay. Also, the paper prove a reliability of proposed protocol through comparison between performance analysis and simulation result of DAP MAC protocol.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.