scholarly journals Estimating Spatio-Temporal Risks from Volcanic Eruptions Using an Agent-Based Model

2020 ◽  
Vol 23 (2) ◽  
Author(s):  
J Jumadi ◽  
Nick Malleson ◽  
Steve Carver ◽  
Duncan Quincey
Keyword(s):  
Volcanic Eruptions ◽  
Agent Based Model ◽  
Agent Based ◽  
Spatio Temporal

scholarly journals Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model

2021 ◽  
Vol 10 (2) ◽  
pp. 88
Author(s):  
Dana Kaziyeva ◽  
Martin Loidl ◽  
Gudrun Wallentin
Keyword(s):  
Regional Scale ◽  
Evidence Base ◽  
Wide Field ◽  
Traffic Patterns ◽  
Agent Based Model ◽  
Validation Data ◽  
Agent Based ◽  
Mobility Behavior ◽  
Spatio Temporal ◽  
Models Validation

Transport planning strategies regard cycling promotion as a suitable means for tackling problems connected with motorized traffic such as limited space, congestion, and pollution. However, the evidence base for optimizing cycling promotion is weak in most cases, and information on bicycle patterns at a sufficient resolution is largely lacking. In this paper, we propose agent-based modeling to simulate bicycle traffic flows at a regional scale level for an entire day. The feasibility of the model is demonstrated in a use case in the Salzburg region, Austria. The simulation results in distinct spatio-temporal bicycle traffic patterns at high spatial (road segments) and temporal (minute) resolution. Scenario analysis positively assesses the model’s level of complexity, where the demographically parametrized behavior of cyclists outperforms stochastic null models. Validation with reference data from three sources shows a high correlation between simulated and observed bicycle traffic, where the predictive power is primarily related to the quality of the input and validation data. In conclusion, the implemented agent-based model successfully simulates bicycle patterns of 186,000 inhabitants within a reasonable time. This spatially explicit approach of modeling individual mobility behavior opens new opportunities for evidence-based planning and decision making in the wide field of cycling promotion

scholarly journals A Conceptual Design of Spatio-Temporal Agent-Based Model for Volcanic Evacuation

Systems ◽  
2017 ◽  
Vol 5 (4) ◽  
pp. 53 ◽  
Author(s):  
Jumadi ◽  
Steve Carver ◽  
Duncan Quincey
Keyword(s):  
Conceptual Design ◽  
Agent Based Model ◽  
Agent Based ◽  
Spatio Temporal

scholarly journals An Agent-Based Evaluation of Varying Evacuation Scenarios in Merapi: Simultaneous and Staged

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 317
Author(s):  
Jumadi Jumadi ◽  
Steve J. Carver ◽  
Duncan J. Quincey
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Relative Effectiveness ◽  
Regional Scale ◽  
Traffic Density ◽  
Peak Time ◽  
Agent Based Model ◽  
Merapi Volcano ◽  
Agent Based ◽  
Spatio Temporal

Mass evacuation should be conducted when a disaster threatens within a regional scale. It is reported that 400,000 people were evacuated during the last eruption of Merapi Volcano in 2010. Such a large-scale evacuation can lead to chaos or congestion, unless well managed. Staged evacuation has been investigated as a solution to reducing the degree of chaos during evacuation processes. However, there is a limited conception of how the stages should be ordered in terms of which group should move first and which group should follow. This paper proposes to develop evacuation stage ordering based on the geographical character of the people at risk and examine the ordering scenarios through an agent-based model of evacuation. We use several geographical features, such as proximity to the hazard, road network conditions (accessibility), size of the population, and demographics as the parameters for ranking the order of each population unit in GIS. From this concept, we produced several scenarios of ranking based on different weightings of the parameters. We applied the scenarios in an agent-based model of volcanic evacuation experiment to observe the results. Afterwards, the results were evaluated based on the ability to reduce the risk and spatio-temporal traffic density along road networks compared to the result of simultaneous evacuation to establish the relative effectiveness of the outcome. The result shows that the staged scenario has a better ability to reduce the potential traffic congestion during the peak time of the evacuation compared to the simultaneous strategy. However, the simultaneous strategy has better performance regarding the speed of reducing the risk. An evaluation of the relative performance of the four varying staged scenarios is also presented and discussed in this paper.

scholarly journals Transmission of Respiratory Infectious Diseases between Neighboring Cities using Agent-based Model and Compartmental Model

2020 ◽  
Author(s):  
Christian Alvin H. Buhat ◽  
Destiny SM. Lutero ◽  
Yancee H. Olave ◽  
Monica C. Torres ◽  
Jomar F. Rabajante
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Compartmental Model ◽  
Preventive Measures ◽  
Agent Based Model ◽  
Agent Based ◽  
Social Distancing ◽  
Spatio Temporal ◽  
Set Up ◽  
Aid Decision

AbstractWe formulate an agent-based model and a compartmental model (SEIR) that simulate the spread of a respiratory infectious disease between two neighboring cities. We consider preventive measures such as implementation of social distancing and lockdown in a city, as well as the effect of protective gears or practices. The chance of travelling to another city and within the city during lockdown, and initial percentage of exposed and infected individuals on both cities influence the increase in the number of newly-infected individuals on both models. Our simulations show that (i) increase in exposed individuals results in increase in number of new infections, hence the need for increased testing-isolation efforts; (ii) protection level of 75-100% effectiveness impedes disease transmission; (iii) travelling within city or to other city can be an option given that strict preventive measures (e.g., non-pharmaceutical interventions) are observed; and (iv) the ideal set-up for neighboring cities is to implement lockdown when there is high risk of disease local transmission while individuals observe social distancing, maximizing protective measures, and isolating those that are exposed. The results of the agent-based and compartmental models show similar qualitative dynamics; the differences are due to different spatio-temporal heterogeneity and stochasticity. These models can aid decision makers in designing infectious disease-related policies to protect individuals while continuing population movement.

scholarly journals AN AGENT-BASED MODEL TO REPRESENT SPACE-TIME PROPAGATION OF FOREST-FIRE SMOKE

2018 ◽  
Vol IV-4 ◽  
pp. 207-212 ◽  
Author(s):  
A. K. Smith ◽  
S. Dragicevic
Keyword(s):  
Particulate Matter ◽  
Complex Systems ◽  
Forest Fire ◽  
Airborne Particulate Matter ◽  
Fire Season ◽  
Agent Based Model ◽  
Airborne Particulate ◽  
Agent Based ◽  
Fire Smoke ◽  
Spatio Temporal

<p><strong>Abstract.</strong> Agent-based modeling approaches have been used for various case studies related to the geospatial dynamics of complex systems. The proliferation of forest-fire smoke and the associated airborne particulate matter that behaves as complex systems make it important to develop reliable geospatial models that can simulate the propagation process to avoid impacts to human health and the environment. Therefore, the main objective of this research study is the development and implementation of an agent-based model (ABM) for the propagation of forest-fire smoke and other airborne particulate matter for use in studying patterns of spatio-temporal propagation. The developed ABM operates on a two-dimensional plane in the landscape where agents representing forest fires emit agents representing smoke. These smoke agents propagate through the study area based on measured atmospheric conditions. The model was developed using data from the 2017 forest fire season in British Columbia (BC) and parts of Alberta, Canada, particularly during the period August 10th&amp;ndash;25th. The obtained simulation results provided patterns of spatio-temporal propagation of fire smoke over large areas of BC and Alberta, and were compared to the real smoke patterns covering the Edmonton metropolitan area, Canada on a similar date. The developed agent-based model can be used to support the emergency planning and decision-making process such as in regulating forest fire evacuations and in the prevention of health problems triggered by the exposure to smoke.</p>

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