• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.334-334
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• 2023

도시침수는 사회 기반시설에 파괴적인 영향을 끼치고, 재산 및 인명 피해의 원인이 되므로, 고해상도 고정확도 예측 정보를 활용한 선제적 대응이 중요하다. 하지만, 기후변화로 인한 강수 강도의 증가, 도시의 확장 및 고밀화 등 토지피복 변화, 홍수방어시설의 노후화 등 여러 요인들의 복합적인 영향으로 인해 도시침수의 정확한 재현 및 예측은 여전히 난제로 남아 있다. 천수 방정식(Shallow Water Equations)을 기반으로 하는 물리과정 모형은 신뢰도 높은 예측 결과를 제공할 수 있지만, Courant-Friedrichs-Lewy 조건 등의 제약으로 인해 대규모 도시 지역의 고해상도 실시간 예측에는 적합하지 않은 한계가 있다. 본 연구에서는 상대적으로 간단한 연산 규칙의 중첩을 통해 복잡계 물리 시스템을 모의하는 셀룰러 오토마타(Cellular Automata; CA) 기술에 기반한 도시침수 해석 모형인 CA-Urban을 개발하고, 미국 Oregon 주 북서쪽에 위치한 Portland시의 도심지역에 대해 침수해석의 적용성을 평가한다. 세부적으로는, 기존 셀룰러 오토마타 기반 침수해석알고리즘의 수치 진동(Oscillation) 문제에 대한 원인을 분석하고, 안정성 향상 방법인 셀 간 최대유량 제한, 가중치 적용 기법, 모형의 계산 효율성 향상을 위한 최적 적응 시간 단계 기법(Adaptive time step)의 적용 결과를 소개한다. 또한, 침투 및 증발산 등 물순환 요소 해석 모듈의 개발 성과 및 방향에 대해서 토의한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.785-791
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• 2011

Two-lane and two-way traffic flow shows various dynamic relationships according to the behaviors of low-speed vehicle and overtaking. And it is essential to develop a vehicle model which simultaneously explains the behaviors of low-speed vehicle and overtaking using opposite lane in order to microscopically analyze various two-lane and two-way traffic flows by traffic flow simulation. In Korea, some studies for car-following and lane-changing models for freeway or signalized road have been reported, but few researches for the development of vehicle model for two-lane and two-way highway have been done. Hence, a microscopic two-lane and two-way vehicle model was, in this study, developed with the consideration of overtaking process and is based on CA (Cellular Automata) which is one of discrete time-space models. The developed model is parallel combined with an adjusted CA car-following model and an overtaking model. The results of experimental simulation showed that the car-following model explained the various macroscopic relationships of traffic flow and overtaking model reasonably generated the various behaviors of macroscopic traffic flows under the conditions of both opposite traffic flow and stochastic parameter to consider overtaking. The vehicle model presented in this study is expected to be used for the simulation of more various two-lane, two-way traffic flows.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.118-125
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• 2004

The purpose of this study is to decide an appropriate neighborhood and a transition rule of cellular automata by analyzing the past growth process of urban areas in Gimhae. With cellular automata which can manage the change based on the dynamic model and time, this study analyzes the urban growth of Gimhae from 1987 to 2001. Also, through the simulation of different types for neighborhood and transition rules, we can find the appropriate neighborhood and the transition rule for Gimhae. In conclusion, the forecast of physical urban growth pattern is more accurate under conditions when the number of matrixes for the neighborhood is small, the shape of the neighborhood is rectangular, "${\alpha}$" value, which control the pace of urban growth, is low and the transition possibility ($P_{ij}$) is high.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.147-158
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• 2004

A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

• Korean System Dynamics Review
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• v.1 no.1
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• pp.133-157
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• 2000

This paper deals with the social system from the point of system thinking consisting the fundamental construct of system dynamics. The Bertalanffy's general system theory, having been criticized because of its ambiguity, and the complex science theory, emerging system theory, are integrated by using the system thinking which is characterized with three concepts, 'feedback thinking', 'dynamic thinking', 'operational thinking'. In the integration, system thinking suggests the dynamic pattern of the social system have not only an equilibrium status but also complex status. The science of complexity gives an implication to system dynamics the important of the uncertainty and complexity if we interpret the social system as an open system. To show more concrete description, I simulate the cooperation model based on the iterated prisoner dilemma. The simulation results show the diverse patterns of cooperation and betrayal. Especially the sensitivity of initial payoff will cause the chaotic strategic landscapes as the game gose on. These results mean that we should not give the hasty prescription to control social system artificially. Because social system retains the self-organizing force in itself.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.1-9
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• 2008

Recently, various researches have been studied on the predict method of land change according to its development. The Cellular Automata(CA) is one of the most popular methods in the urban growth modeling. The basis principle of CA is to repeat operations, which convert the current cell into new cell state by the transaction rule. It will minimize the loss of data by using Fuzzy-AHP and it can lead the flexible urban growth modeling. However, AHP would have a disadvantage to repeat the procedure of the collecting intentions until it derives the weight. Also, it is necessary for the simulation of CA to repeat the operations and the test of data accuracy should be accompanied. The purpose of this study is to predict the Busan city growth model and analyze it according to the automated test method by applying CA as well as Fuzzy-AHP. This study shall improve the difficulties caused by complexity and repetitiveness in the urban grow modeling. The practical modeling could be derived from the verification, and the derived modules could be applied to the similar case studies.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.23-29
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• 2012

Existing pedestrian and evacuation models generally seek to find locally optimal solutions for the shortest or the least time paths to exits from individual locations considering pedestrian's characteristics (eg. speed, direction, sex, age, weight and size). These models are not designed to produce globally optimal solutions that reduce the total evacuation time of the entire pedestrians in a building when all of them evacuate at the same time. In this study, we suggest a globally optimal model for indoor pedestrian evacuation to minimize the total evacuation time of occupants in a building considering different distributions of them. We used the genetic algorithm, one of meta-heuristic techniques because minimizing the total evacuation time can not be easily solved by polynomial expressions. We found near-optimal evacuation path and time by expressing varying pedestrians distributions using chromosomes and repeatedly filtering solutions. In order to express and experiment our suggested algorithm, we used CA(cellular automata)-based simulator and applied to different indoor distributions and presented the results.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.61-68
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• 2010

토지피복은 대부분의 수문 수질 모형의 중요한 매개변수로서, 수자원 변화 예측에 중요한 입력자료로 활용되고 있다. 본 연구에서는 개선된 CA (Cellular Automata)-Markov 기법을 이용하여 충주댐유역의 미래 산림식생변화에 대한 예측을 시도하였다. 예측과정으로 과거의 Landsat TM 영상 (1985, 1990, 1995, 2000)을 이용하여 기법의 정확도 검증 및 산림분포의 변화경향을 파악하고, Landsat 산림은 2000년과 2005년의 NOAA AVHRR NDVI값을 기준으로 침엽수림, 혼효림, 활엽수림의 3종으로 구분한 후, 이를 이용하여 2030년, 2060년, 2090년의 식생변화를 추정하는 방법을 제안하였다. 이 방법의 적용결과, 2000년과 비교하여 2090년의 활엽수림과 혼효림은 각각 14.3 %, 11.6 % 증가하였으며, 침엽수림은 24.9 % 감소하는 것으로 나타났다. 과거의 경향성에 의해 예측을 시도한 본 연구결과는 미래 토지피복 변화에 따른 수문 수질 영향 분석시 지표 조건의 불확실성을 줄이는데 활용될 수 있다고 판단된다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.459-465
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• 2000

최근 들어 인공지능과 뇌과학 분야의 연구성과를 힘입어 뇌의 기본기능을 이해하고 재구축하고자 하는 시도가 활발히 전개되고 있다. 뇌의 정보처리 기능을 실험관찰 방법으로 밝히고자 하는 신경과학, 마음의 정보 처리 기능을 역시 실험관찰 방법으로 이해하고자 하는 심리학, 그리고 정보처리모형의 구성법을 제시하는 컴퓨터과학을 통합함으로써 뇌와 마음의 작동을 정보과학의 입장에서 해명하고자 하는 접근방식이 현재 가장 가능성이 있다고 생각된다. 본 논문에서는 그와 같은 맥락에서 인공적으로 뇌를 구현하기 위하여 제안된 CAM-Brain을 소개하고, 로봇을 제어하는 문제에 적용한 예를 통하여 그 가능성을 보이고자 한다.