Abstract
When large-scale disasters occur, evacuees have to evacuate to safe places quickly. They, however, may not be able to afford to obtain sufficient information for their evacuations under such emergent situations. In this paper, we propose an automatic evacuation guiding scheme using evacuees’ mobile nodes, e.g., smart phones. The key idea to achieve automatic evacuation guiding is implicit interactions between evacuees and their mobile nodes. Each mobile node tries to navigate its evacuee by presenting an evacuation route. At the same time, it can also trace the actual evacuation route of the evacuee as the trajectory by measuring his/her positions periodically. The proposed scheme automatically estimates blocked road segments from the difference between the presented evacuation route and the actual evacuation route, and then recalculates the alternative evacuation route. In addition, evacuees also share such information among them through direct wireless communication with other mobile nodes and that with a server via remaining communication infrastructures. Through simulation experiments, we show that 1) the proposed scheme works well when the degree of damage is high and/or road segments are continuously blocked, 2) the average evacuation time can be improved even in small penetration ratio of the proposed system, and 3) the direct wireless communication can support many evacuations at almost the same level as the communication infrastructure when the number of evacuees becomes large.
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This paper is an expanded version of the paper presented at The 12th International Conference on Mobile Web and Intelligent Information Systems (MobiWis 2015) [9] . This research was partly supported by Strategic Information and Communication R&D Promotion Programme (SCOPE) of Ministry of Internal Affairs and Communications, and JSPS KAKENHI Grant Number 15H04008, Japan.
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Komatsu, N., Sasabe, M., Kawahara, J. et al. Automatic evacuation guiding scheme based on implicit interactions between evacuees and their mobile nodes. Geoinformatica 22, 127–141 (2018). https://doi.org/10.1007/s10707-016-0270-1
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DOI: https://doi.org/10.1007/s10707-016-0270-1