Earticle

교통 시뮬레이션 모형은 실제 교통 네트워크를 모형으로 구현하여 여러 가지 교통정책을 평가하는 데에 사용된다. 이 때 모형이 실제의 교통현상을 잘 반영했는지 여부를 판단하는 모형 검증 절차는 가장 중요한 절차 중 하나이며 모형 검 증에는 실측 교통량과 속도 등이 주로 사용된다. 본 연구에서는 노스캐롤라이나 랄리에 있는 I-40 고속도로 상에서 일어 나는 심각한 오후 첨두 병목현상을 DYNASMART-P라는 메조스코픽 교통 시뮬레이션 모형으로 구현한 결과를 검증하고 자 하였다. 연구 대상 축의 경우 노스캐롤라이나 교통국(NCDOT)의 교통정보센타에서 속도검지기를 설치하여 온라인으 로 속도를 수집하고 있다. 그러나 검지기 측정 자료는 지점속도이고 시뮬레이션 모형의 결과값은 링크 평균속도이므로 모형 검증에 사용하기에는 적합하지 않다. 따라서, 본 연구에서는 GPS 장비를 활용하여 통행시간을 측정하여 모형에서 의 통행시간과 비교함으로써 시뮬레이션 모형의 결과를 검증하였다. 이 논문에서는 데이터 수집, 모형검증 절차 및 결과 를 서술하였다.

Traffic simulation models have been used for assessing various transportation strategies. Through comparing results from a simulation model and real field data, researchers try to show how close the model can reproduce the real world traffic. This model verification step is one of the most essential tasks in modeling procedure. Traffic counts and speeds have been frequently used for the verification or validation. Authors modeled severe PM peak bottleneck situation on the I-40 corridor in Raleigh, North Carolina using DYNASMART-P, a mesoscopic traffic simulation tool and verified the model. NCDOT has Traffic Information Management System which has archive capability for the traffic speeds on the I-40 corridor. However, the authors selected travel time as the field measure for model verification and collected the data using a GPS equipment because the speed data from NCDOT speed detectors are spot speeds which are not appropriate for comparison with link average speed from the simulation model. This paper describes the GPS field data collection procedure, the model verification method, and the results.

정부는 교통운영체계 선진화를 위하여 지속적인 교통시설 및 운영방식 개량, 그리고 교육 및 단속 등을 실시하여 왔다. 그러한 많은 노력에도 불구하고 우리나라 교통신호와 도로운영체계가 불합리하다는 지적이 지속적으로 제기되어 왔다. 이러한 원인 중에 하나는 정부가 제시한 대안들에 대하여 체계적이고 과학적인 사전 평가가 부족하였기 때문이다. 또한, 다양한 교통운영체계 대안에 대한 이동성 및 안전성을 종합적으로 분석할 수 있는 도구가 부족하였다. 따라서, 본 연구에서는 이러한 종합적인 평가 도구로써 미시교통분석모형의 체계적인 활용을 제안하며, 분석사례로 공용 좌회전 차로에 중첩현시가 적용 중인 대상교차로는 다양한 시나리오 하에서 안전성과 이동성을 평가하였다. 그 결과 공용 좌회전 차로에서 중첩현시의 적용은 이동성은 큰 차이가 없으나 안전성 측면에서 불리한 것으로 나타났다. 또한 전체 및 직진교통량 증가를 가정한 민감도 분석에서는 중첩현시가 가장 좋은 이동성을 보이나 안전성 측면에서 크게 나빠지는 것을 계량적으로 증명하였다.

Government agencies including the national police agency have executed diverse efforts including continuous improvements of traffic facilities and operation methods, education, enforcements in order to improve traffic operation systems; nevertheless there have been continuous criticisms on irrationality in traffic signal and road facility operation. One of the reasons may be the lack of systematic preliminary evaluations on various alternatives. However, there was no appropriate tool to evaluate the mobility and safety of thus alternatives in a systematic way. Therefore, this study proposes the systematic use of microscopic traffic simulation models as a comprehensive evaluation tool. In addition, this study verified the potential of using a microscopic traffic simulation model using the case of operating an overlap phase on a shared-left-turn lane through a systematic way where the evaluation was conducted through data collection, building networks, calibrating microscopic simulation models, producing performance measures, evaluating mobility and safety, and so on. As a result, the operation of overlap phase on a shared-left-turn lane showed no big difference from other operation scenarios such as leading left-turn on exclusive left turn lane in terms of mobility. However the operation of overlap phase on a shared-left-turn lane decreased safety by increasing potential conflicts.

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.

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.

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.

The road sign in dynamic traffic system is an important element which affects on human cognitive performance on driving. Web-based vision system simulator was developed to examine the cognition time of the road sign in dynamic environment. This experiment was designed in within-subject design with two factors; vehicle speed and the amount of information of the traffic sign. It measured the cognition time of the road sign through two evaluation methods; the subjective test with vision system simulator and computational cognitive model. In these two evaluations of human cognitive performance under the dynamic traffic environment, it demonstrated that subject's cognition time was affected by both the amount of information of traffic sign and driving speed.

There are plenty of optimization models for the signal-system of a single intersection and area traffic. Some of those models are adopted for the real traffic signal control system. The simulators for a single crossroad have been developed, so that we could evaluate optimization models and traffic control systems. However, the simulators for the area traffic are still being developed. Therefore, there are some limitations in the analysis and evaluation for area traffic control systems, The area traffic is consist of several intersections interconnected which are very complicated and many traffic strategy are adopted for the control system. This paper features an effective area traffic control system by High Lever Architecture(HLA) which is a new developed simulation tool. In this paper, we discuss the design of HLA-based area traffic control simulation. We describe technical motivations for the HLA, the key elements of the architecture and how they are minimum and essential to the goal of reuse and interoperability.

군경 해양데이터는 국가 안보 및 해상 안전 임무에 필수적이지만, 보안 제약으로 외부 활용이 제한되어 기술 검증에 어려움이 있다. 본 연구는 이러한 한계를 극복하기 위해 에이전트 기반 해상교통 시뮬레이션 모델 설계 방안을 제시한다. 제안 모델은 선박항해 에이전트와 수로환경 에이전트로 구성되며, 각각 자율 기동과 해양환경 정보 제공 기능을 수행한다. 선박항해 에이전트는 Nomoto 모델과 강화학습 기반 정책 결정 알고리즘을 적용하여 충돌 회피 기능을 구현하고, 수로환경 에이전트는 항행 지형, 수심, 조위, 조류 정보를 실시간으로 제공한다. 또한, 모델 간 상호 운용성을 확보하기 위해 FMI 표준을 적용하여 다양한 시뮬레이션 환경에의 통합과 재사용이 가능하도록 하였다. 본 연구는 제한된 정보 환경에서도 시뮬레이션 기반 분석과 기술 검증이 가능한 구조를 제시하였으며, 향후 실환경 적용 기반 마련에 기여할 수 있다.

Military and security marine data are crucial for national security and maritime safety missions. However, security restrictions hinder their external use, complicating technology validation. This study proposes a design framework for an agent-based maritime traffic simulation model to address these challenges. The proposed model includes two key components: a ship navigation agent and a hydrographic environment agent. The ship navigation agent autonomously maneuvers using a collision avoidance system based on the Nomoto model and a reinforcement learning-based decision algorithm. Meanwhile, the hydrographic environment agent supplies real-time information about navigational features, water depth, tides, and currents. Additionally, the FMI standard is employed to ensure interoperability between models, facilitating integration and reuse across various simulation environments. This study offers a structure for simulation-based analysis and technology validation, even under restrictive information conditions, laying the groundwork for future real-world applications.

본 연구는 DEVS를 기반으로 개발된 교통류 시뮬레이션 시스템인 $\ulcorner$I$^3$D$^2$ 교통류 시뮬레이션 시스템$\lrcorner$(이하 I$^3$D$^2$)의 검증을 그 목적으로 한다. I$^3$D$^2$는 본 연구진이 DEVS를 기반으로 개발한 범용 시뮬레이션 도구로써, 이미 서울시 강남 신호교차로와 내부순환로를 대상으로 하여 개발된 내용을 발표한 바 있다. I$^3$D$^2$는 헌재 단속류에서의 최적신호 생성 및 대기행렬 예측 문제, 그리고 연속류 시설의 용량 산정 문제등을 시뮬레이션 할 수 있다. 하지만 아직 문헌자료나 현장 데이터를 토대로 한 충분한 검증이 수행되지 못한 문제가 있다. 따라서 본 연구에서는 문헌자료를 토대로, I$^3$D$^2$를 검증한다. 이를 위하여 고속도로 또는 도시고속도로와 같은 연속 교통류의 대표적인 효과척도인 $\ulcorner$교통량 - 밀도 - 평균주행속도 (시간)$\lrcorner$ 간의 상관관계를 이용하여 미국 HCM과 우리나라의 도로용량편람에 정의되어 있는 기준을 토대로 I$^3$D$^2$ 검증을 수행하였다. 모델링은 서울시 올림픽대로의 양화대교 - 성산대교 - 가양대교 구간을 대상으로 했으며, 검증은 교통량에 따라 크게 3가지 교통류 상태(random, intermediate, constant)를 기준으로 시뮬레이션이 각각의 교통상태에서 예측한 평균주행시간의 정확도를 측정하면서 수행하였다. 검증 결과 random 상태에서는 문헌자료에 부합되는 예측결과를 보여주었으나, intermediate와 constant 상태에서는 문헌보다 다소 낮은 속도를 보여주었다 이러한 속도차는 추후 현장 데이터를 수집하여 보다 실질적인 검증을 통하여 조정되어야 할 것으로 판단된다.

Many studies have been performed and applied successfully for the control of undersaturated intersections, but most of them have been ineffective or invalid in oversaturated conditions. There has been relatively limited research in traffic control for oversaturated environments, and most has been too theoretical to be applied in a real system. Therefore, a traffic simulation model specifically designed for oversaturated arterial networks was developed. Two control objectives of traffic signal timing in oversaturated conditions were taken into consideration. One was to maximize the throughput, or the number of vehicles processed during a given time period. The other was to prevent queue spillback or to minimize the occurrence of queue spillback if inevitable.

본 연구에서는 거시적 연속교통류 모형에 바탕을 둔 도시고속도로로 시뮬레이션모형의 개발이 시도되었다. 이 모형은 simple continuum model에 통행수요모형 기능을 강화시킨 것으로서 기존 연속교통류 시뮬레이션모형의 단점을 개선하였다. 제안된 시뮬레이션모형은 정산과정을 거쳐 미국 도시고속도로에서 수집한 현장자료에 의해 평가되었다. 특히 링크의 목적지별 차량대수 추정, 실시간 O-D추정의 문제가 확장칼만필터의 형태로 접근되었으며, 개발된 시뮬레이션모형을 ATMS전략에 활용하는 방안이 개발·평가되었다. 이들 전 과정을 통합한 모수적응적 모형(Parameter Adaptive Model)에 의해 교통량을 실시간으로 예측(Real time traffic prediction)하는 방법을 제안하였으며 현장자료에 의해서 평가되었다.

본 연구는 GIS를 이용하여 미시적 수준에서 교통현상을 시뮬레이션 할 수 있는 미시적 수준의 교통모형을 설계 및 구현하는데 목적이 있다. 이를 위해 차량이 GIS 도로 중심선 자료를 차선, 이동속도 등이 반영된 도로 네트워크 자료로 인식하는 방법론을 개발하였으며, 운전자의 주행 행태를 반영하기 위해 환경인식모형, 차두시간분포모형, 차량추종모형 및 차로변경모형으로 행태모형을 설계 및 구현했다. 모형의 정확도 평가는 종로구의 자하문길을 대상으로 관측자료와 예측 자료를 비교하였으며, 그 결과 시간대별 이동 속도를 매우 정확하게 예측한 것을 확인할 수 있었다. 본 연구를 통해 구현된 GIS 기반의 미시적 수준의 교통모형은 교통 탄소 배출량 분석, 교통류 평가 및 도시기반시설 입지 계획등의 다양한 분야에 효과적으로 기여할 수 있을 것으로 판단된다.

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

PURPOSES : This study performs fundamental research on ramp-metering design criteria. METHODS : We carefully review previous studies in terms of ramp-metering design criteria and then consider applicability in Korea. For this, traffic simulation model is employed to analyze actual effect according to specific location of stop-line when implementing ramp-metering. RESULTS : When a stop-line moving forward with a 50m interval, travel speed at mainline relative to current stop-line location tends to decrease. However, traveling speed at approach roads increase about 5~18% under the same condition. When a stop-line location moving backward with a 50m interval, mainline travel speed increase approximately 17~32% whereas traveling speed at approach roads decrease. All cases are compared with the current stop-line location. CONCLUSIONS : We believe that both cases are useful with respect to freeway management. For example, moving forward a stop-line case can be used management for queuing area at ramp section and approach roads. Moving backward a stop-line case can be used for traffic control, focusing on mainline of freeways.