• 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.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.87-92
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• 1999

교차로 접근지체의 산정은 간선도로의 서비스수준 평가에 있어서 가장 중요한 요소 중의 하나이다. 교차로 접근지체는 상류부 교차로에서 진입하는 교통에 대한 균일지체와 그 이외 단일로 상에 존재하는 세가로등에서 유입되는 교통에 대한 무작위지체, 1회의 신호주기에 교차로를 통과하지 못한 교통에 대한 잔여지체 등과 연동보정계수를 이용하여 산정된다. 우리나라를 비롯한 대부분의 나라에서는 미국에서 차량의 지체와 연동보정계수를 이용하여 개발된 교차로 접근지체 산정식의 구조를 그대로 수용하고 있다. 그러나 도심부 신호교차로 사이의 단일로에 보행자를 위한 횡단신호가 설치되어 있는 경우, 이러한 단일로 횡단신호가 하류부 교차로의 접근지체에 미치는 영향이 있을 것으로 판단한다. 따라서 미국과는 달리 신호교차로간의 간격이 크고, 단일로 상에 보행자용 횡단시호 설치가 빈번한 우리나라의 실정에서는 이에 대한 영향을 분석하여 교차로 접근지체 산정 시 이를 반영하는 것이 바람직하다. 본 연구에서는 단일로 횡단신호가 하류부 신호교차로에서의 접근지체에 미치는 영향을 분석하기 위하여, 상류부 교차로와 단일로 중간부 횡단보도와의 거리, v/c 비, 신호 offset 등 상황을 설정하여 TRANSYT-7F를 이용하여 시뮬레이션을 수행하였다. 본 연구에 의하면 단이로 중간의 횡단신호가 상류부 교차로의 신호와 연동되지 않는 경우에는 하류부 교차로의 접근지체에 미치는 영향이 거의 없는 것으로 나타났으며, 연동 시에는 상류부 교차로와의 거리, v/c 비, 신호 offset 등에 따라 최고 80% 이상 까지 접근지체가 증가하였다. 일반적으로 신호 offset이 40%에서 60% 사이로 연동상태가 불량할수록 하류부 교차로에서의 접근지체가 증가하는 것으로 나타났으며, 그 외에 변수에 대하여서도 신호 offset에 따라 다른 정도로 접근지체에 영향을 미치는 것으로 나타났다. 따라서 현재 우리나라의 신도시 개발 시 일반적으로 나타나는 대규모 구획(super block)과 이로 인하여 불가피한 단일로 중간부의 횡단신호의 설치는 교통운영 측면에서 재고되어야 할 것으로 판단된다.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.25-34
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• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.115-129
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• 2001

The purpose of this study is to develop a cycle-free signal timing model for minimizing delays based on Third-generation control concept using Genetic Algorithm. A special feature of this model is its ability to manage delays of turning movements on the cycle basis. The model produces a cycle-free based signal timing(cycles and green times) for each intersection to minimize delays of turning movements on the cycle basis. The performance of cycle-free signal timings was evaluated on normal (v/c = 0.7) and oversaturated (v/c=1.0) conditions. The performance measures are throughput and the number of queued vehicles at the end of green time. The result shows that the cycle free signal timing is superior to the fixed signal timing to manage traffic flows of intersections; (1) the proposed model accomplishes the basic objective of the research, producing cycle free signal timings on the cycle basis, (2) on normal conditions, cycle free signal timings produce less queued vehicles at the end of green time, and (3) on oversaturated conditions, the cycle free signal timing is superior to the fixed signal timing to manage saturated traffic flows of intersections.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.145-157
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• 2004

The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.