Planning for tourist urban evacuation routes: A framework for improving the data collection and evacuation processes

Guy Wachtel, Jan-Dirk Schmöcker, Yuval Hadas, Yuhan Gao, Oren E Nahum and Boaz Ben-Moshe
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Guy Wachtel: Bar-Ilan University, Israel
Jan-Dirk Schmöcker: Kyoto University, Japan
Yuval Hadas: Bar-Ilan University, Israel
Yuhan Gao: Kyoto University, Japan
Oren E Nahum: Bar-Ilan University, Israel; Ashkelon Academic College, Israel

Environment and Planning B, 2021, vol. 48, issue 5, 1108-1125

Abstract: Tourism is one of the largest growing industries worldwide. As the number of tourists is rapidly increasing, so too are tourist safety concerns. The increasing frequency of natural disasters along with the growth of urban areas makes it even more complex to address the resilience of tourists during such events. This article proposes a framework for collecting information about tourist locations and flows within urban areas and how to use this information for more efficient and safe evacuation routing. We define population behavior models that can be obtained from gathering empirical data and categorize them into three groups. We review the different evacuation scenarios (divided into sudden and predictable scenarios) and the types of information needed in each case. Further, we discuss the complexity of monitoring and forecasting tourists’ movements in the long term and for short-term predictions including the available data sources for doing so. The data gathering and tourist behavior are explained with examples from Kyoto, Japan, a major tourist attraction and a location that is prone to disasters. Finally, technological solutions for better guidance during the evacuation process of the population are discussed, including low-tech ones and advanced options such as websites, apps and Bluetooth Low Energy sensors, where the last one is demonstrated by a navigation experiment in a 3D environment.

Keywords: Tourist evacuation planning; flow pattern prediction; data collection and provision (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:48:y:2021:i:5:p:1108-1125

DOI: 10.1177/2399808321994575

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