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Safety Forecasting and Early Warning of Highly Aggregated Tourist Crowds in China

Jie Yin,Yahua Bi,Xiangmin Zheng,Ruey-Chyn Tsaur

Published 2019 in IEEE Access

ABSTRACT

With tourism development in China, the influx of tourists in popular tourist attractions has become more frequent. However, space cannot accommodate such a large influx of tourists. Through empirical testing, this research identified 23 variables that influence the safety of tourists in crowded spaces. We divided 23 variables into three factors: pressure factors, state factors, and crowd management actions. Based on the data collected, this study proposes a system model that includes a feedback mechanism to evaluate the safety of highly aggregated tourist crowds (HATCs) and identify moments requiring security warnings. System simulation results showed that the safety level of HATCs presented a complex process of change in different situations. Thus, management can take corrective actions. We tested this model by simulating different crowding conditions and assessing the safety level of tourists. Different warning plans were proposed based on the simulated security level.

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