Intelligent Emergency Evacuation Model for West Lake Scenic Area Based on Path-Flow Feedback Network and Evacuation Cost

Lin Zhang; Xingqi Wang; Xiaoqing Feng; Jianing Ye; Weijie Wang

doi:10.2991/978-94-6463-276-7_12

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Intelligent Emergency Evacuation Model for West Lake Scenic Area Based on Path-Flow Feedback Network and Evacuation Cost

Authors

Lin Zhang¹, Xingqi Wang²^{, *}, Xiaoqing Feng¹, Jianing Ye¹, Weijie Wang¹

¹School of Information Management and Artificial Intelligence, Zhejiang University of Finance & Economics, Hangzhou, China

²Key Laboratory of Discrete Industrial Internet of Things of Zhejiang Province, Hangzhou Dianzi University, Hangzhou, China

^*Corresponding author. Email: xqwang@hdu.edu.cn

Corresponding Author

Xingqi Wang

Available Online 27 October 2023.

DOI: 10.2991/978-94-6463-276-7_12 How to use a DOI?
Keywords: component; evacuation optimization; transit network design; information feedback
Abstract: If a senic spot is too crowded, there will be a stampeded accident. The existing emergency evacuation methods can be divided into two categories. The evacuation model without information feedback develops routes according to the flow of people at the beginning of the model, with high computing efficiency, but does not take into account the irregular movement of tourists. The model with information feedback takes into account the dynamics and adjusts the visitors’ routes in real time, which can achieve the best evacuation effect. In this paper, an intelligent emergency model with information feedback based on runoff feedback and evacuation cost is studied to give a reasonable evacuation method based on actual visitor density and traffic routes in scenic spots, and help visitors choose the best route to achieve evacuation quickly.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
Series: Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date: 27 October 2023
ISBN: 10.2991/978-94-6463-276-7_12
ISSN: 2667-128X
DOI: 10.2991/978-94-6463-276-7_12 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Lin Zhang
AU  - Xingqi Wang
AU  - Xiaoqing Feng
AU  - Jianing Ye
AU  - Weijie Wang
PY  - 2023
DA  - 2023/10/27
TI  - Intelligent Emergency Evacuation Model for West Lake Scenic Area Based on Path-Flow Feedback Network and Evacuation Cost
BT  - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
PB  - Atlantis Press
SP  - 95
EP  - 103
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-276-7_12
DO  - 10.2991/978-94-6463-276-7_12
ID  - Zhang2023
ER  -

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