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Transportmetrica. (Abingdon, Oxfordshire, UK), 2017-10, Vol.5 (4), p.385-401
2017

Details

Autor(en) / Beteiligte
Titel
An evacuation route choice model based on multi-agent simulation in order to prepare Tsunami disasters
Ist Teil von
  • Transportmetrica. (Abingdon, Oxfordshire, UK), 2017-10, Vol.5 (4), p.385-401
Ort / Verlag
Abingdon: Taylor & Francis
Erscheinungsjahr
2017
Link zum Volltext
Quelle
Taylor & Francis
Beschreibungen/Notizen
  • Minimising the damage caused by natural disasters such as tsunamis in vulnerable coastal areas requires the development of an emergency action plan. An evacuation plan can reduce the damaging impact of an unexpected tsunami. One of the most important factors in developing an action plan is a guideline for choosing proper evacuation routes in order to minimise loss of life and property. In this study, an evacuation network is designed to develop an evacuation plan based on a hierarchical network design problem used in communication networks, public transport, and social organisation network designs. Experimental analyses have been carried out in order to find effective evacuation plans at Haeundae Beach, Busan, Korea, using multi-agent transportation simulation (MATSim). In order to design an effective hierarchical evacuation network, a hierarchical evacuation network design is developed using the concepts of hub location, clustering, and network design. Further, we consider contraflow in the evacuation network, as well as determination of corridor lines by the minimum distance rule, maximal flow rule, maximum accessible rule, and minimum travel time rule. As a result of running each scenario using MATSim, a criterion for establishing the corridor line is evaluated. An optimal evacuation route is found to minimise overcrowded queues of evacuees, when the total evacuation time from the area of the tsunami is approximately 3 hours and 30 minutes.
Sprache
Englisch
Identifikatoren
ISSN: 2168-0566
eISSN: 2168-0582
DOI: 10.1080/21680566.2016.1147002
Titel-ID: cdi_informaworld_taylorfrancis_310_1080_21680566_2016_1147002

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