6,614 research outputs found

    OpenKnowledge at work: exploring centralized and decentralized information gathering in emergency contexts

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    Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial; ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support centralized as well as decentralized architectures for information gathering. For this purpose we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases

    Key challenges in agent-based modelling for geo-spatial simulation

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    Agent-based modelling (ABM) is fast becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation tuned to London data which elaborates the standard Schelling (1971) model, and an agent-based residential location built according to spatial interactions principles, calibrated to trip data for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions

    Modelling shared space users via rule-based social force model

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    The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design and achieve solutions for optimal design features before implementation. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since vehicle movements are not as flexible as pedestrian movements, velocity angle constraints are included for vehicles. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs

    A Conceptual Design of Spatio‐Temporal Agent‐ Based Model for Volcanic Evacuation

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    The understanding of evacuation processes is important for improving the effectiveness of evacuation plans in the event of volcanic disasters. In terms of social processes, the enactment of evacuations in volcanic crises depends on the variability of individual/household responses. This variability of population response is related to the uncertainty and unpredictability of the hazard characteristics of volcanoes—specifically, the exact moment at which the eruption occurs (temporal), the magnitude of the eruption and which locations are impacted (spatial). In order to provide enhanced evacuation planning, it is important to recognise the potential problems that emerge during evacuation processes due to such variability. Evacuation simulations are one approach to understanding these processes. However, experimenting with volcanic evacuations in the real world is risky and challenging, and so an agent‐based model is proposed to simulate volcanic evacuation. This paper highlights the literature gap for this topic and provides the conceptual design for a simulation using an agent‐based model. As an implementation, an initial evacuation model is presented for Mount Merapi in Indonesia, together with potential applications of the model for supporting volcanic evacuation management, discussion of the initial outcomes and suggestions for future work
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