# Congestion Evaluation of Pedestrians in Metro Stations Based on Normal-Cloud Theory
## 5 Conclusions  
At present, the passenger crowd safety of the rail transit station is a big challenge for the development of the urban rail system. It is of great practice to assess the GPC of a metro station accurately and quickly so as to deal with rapid decision-making in emergency circumstances and enhance the ability of evacuation.  
The present study applied the NC model to evaluate the GPC so as to solve the uncertainty and fuzziness nature of the passenger distribution in metro stations. Data were collected in the Ningbo Gulou rail transit station using a video sequence approach. The results showed the effectiveness of the four-grade grading criterion of the GPC and further confirmed the applicability of the NC model in the assessment of GPC. Although the four-grade grading criterion was a special case in this study, the proposed assessing method of the GPC can be used in a universal way to determine the crowding status in metro stations. Furthermore, this study provided several pedestrian safety measures for crowd management.  
This study had some limitations. The survey was only conducted in the city of Ningbo, however, the operations of the urban rail transit system varied across cities. In some cities, such as Beijing, Shanghai, Guangzhou, and Hangzhou, urban rail transit networks have experienced rapid development and large-scale crowd events occur every day. The research method may not be suitable for these networks. To fill the gap, the neural networks approach is recommended in future studies, since neural networks currently provide the best solutions to many problems in automatic control, robot control, artificial intelligence, pattern recognition (i.e., image recognition, speech recognition), signal processing, and natural language processing. Furthermore, different weights for each facility characteristic of the NC model can be considered for further studies. This can help in determining more accurately whether the model is suitable as a standard of measure. Simultaneously, some innovative new measures can be developed.  
**Data Availability:** The data used to support the findings of this study are included within the article.  
**Author Contributions:** Conceptualization, J.Z.; Data curation, J.Z. and Y.W.; Investigation, S.G.; Methodology, J.Z. and S.G.; Resources, S.G. and J.Z.; Supervision, Y.W. and X.M.; Writing--review and editing, J.Z., Y.W., X.M. and M.Z.; Funding acquisition, J.Z. and X.M.  
**Funding:** This study was supported by the Natural Science Foundation of Zhejiang Province (No. LQ19E080003), Philosophy and Social Science Foundation of Zhejiang Province (No. 18 NDJC107 YB), Educational Science Planning of Zhejiang Provincial Education Department (No. 2018 SCG103), Natural Science Foundation of Ningbo Municipality (No. 2018A610127), Humanities and Social Science Research Program of Ministry of Education in China (No. 16 XJCZH002) and the Fundamental Research Funds for the Central Universities (Grant Number 310823170657 and 300102238501).  
**Conflicts of Interest:** The authors declare that there are no conflicts of interest regarding the publication of this paper.