An Evacuation Route Planning for Safety Route Guidance System after Natural Disaster Using Multi-objective Genetic Algorithm

نویسندگان

  • Yukie Ikeda
  • Masahiro Inoue
چکیده

When a natural disaster occurred, some roads cannot be used anymore and sometimes blocked. Also, survivors and refugees cannot follow the evacuation procedures by just using default maps after disaster. A previous study proposed a safety route guidance system that can be used after natural disasters by using participatory sensing. The system estimates safe routes and generates an evacuation map by collecting GPS data and accelerometer data from pedestrians’ smartphone. However, the system does not base on default map data. After that, the system evaluates the safety of each route. However, the previous study did not propose a method of finding evacuation routes from the users’ current location to their destination. Therefore, in this study, we proposed a method of evacuation route planning. We have implemented Multi-Objective Genetic Algorithm (MOGA) into the route planning methodology. The proposed system has three objective functions, which are: evacuation distance, evacuation time and safety of evacuation route. Also, we proposed a new safety evaluation method. As a result, this study gives a better reflection of the change of road conditions. Also, the safety evaluation values are more useful than the previous study’s evaluation method of the route. Moreover, the system can provide evacuation routes with different characteristics to users. As a result, the users can select a route which is suitable for their situation. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of KES International.

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تاریخ انتشار 2016