{"paper":{"title":"Evacuation time estimate for a total pedestrian evacuation using queuing network model and volunteered geographic information","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"physics.soc-ph","authors_text":"Anders Johansson, Bharat Kunwar, Filippo Simini","submitted_at":"2015-10-08T14:14:44Z","abstract_excerpt":"Estimating city evacuation time is a non-trivial problem due to the interaction between thousands of individual agents, giving rise to various collective phenomena, such as bottleneck formation, intermittent flow and stop-and-go waves. We present a mean field approach to draw relationships between road network spatial attributes, number of evacuees and resultant evacuation time estimate (ETE). We divide $50$ medium sized UK cities into a total of $697$ catchment areas which we define as an area where all agents share the same nearest exit node. In these catchment areas, 90% of agents are withi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.03087","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}