Individual-oriented Model Crowd Evacuations Distributed Simulation
Emergency plan preparation is an important problem in building design to evacuate people as fast as possible. Simulation exercises as fire drills are not a realistic situation to understand people behaviour. In the case of crowd evacuations the complexity and uncertainty of the systems increases. Co...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2014 |
| País: | España |
| Recursos: | Universitat Autònoma de Barcelona |
| Repositório: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglês |
| OAI Identifier: | oai:ddd.uab.cat:306171 |
| Acesso em linha: | https://ddd.uab.cat/record/306171 https://dx.doi.org/urn:doi:10.1016/j.procs.2014.05.145 |
| Access Level: | Acceso aberto |
| Palavra-chave: | IoM Distributed Simulations MPI Crowd Evacuations |
| Resumo: | Emergency plan preparation is an important problem in building design to evacuate people as fast as possible. Simulation exercises as fire drills are not a realistic situation to understand people behaviour. In the case of crowd evacuations the complexity and uncertainty of the systems increases. Computer simulation allows us to run crowd dynamics models and extract information from emergency situations. Several models solve the emergency evacuation problem. Individual oriented modelling allows to give behaviour rules to the individual and simulate interactions between them. Due to variation on the emergency situations results have to be statistically reliable. This reliability increases the computing demand. Distributed and parallel paradigms solve the performance problem. In the present work we present a crowd evacuations distributed simulator. We implemented two versions of the model. One using Netlogo and another using C with MPI. We chose a real environment to test the simulator: pavilion 2 of Fira de Barcelona building, able to hold thousands of persons. The distributed simulator was tested with 62,820 runs in a distributed environment with 15,000 individuals. In this work we show how the distributed simulator has a linear speedup and scales efficiently. |
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