Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 5, 25 May 2023


Open Access | Article

How to Reduce Traffic Jams when Flood Happens

Yanning Wu * 1
1 Wuxi No.1 Senior High School, Wuxi, 214031, The People’s Republic Of China

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 5, 334-338
Published 25 May 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yanning Wu. How to Reduce Traffic Jams when Flood Happens. TNS (2023) Vol. 5: 334-338. DOI: 10.54254/2753-8818/5/20230575.

Abstract

Most map applications play the job of navigating users and informing them of traffic jams. However, they often cannot deal with an emergent situation when a disaster such as a flood takes place. This paper aims at providing a solution for map and navigation applications how to ensure users’ safety when natural disasters of floods happen. The subject uses sensors, programming, and perceptrons to prompt the study and take the Beijing-Hangzhou canal as a sample since each river has its warning water levels. Nevertheless, this paper provides a solution to the research aim, no experiments are involved.

Keywords

flood risk, traffic, GPS.

References

1. Jingxuan Zhu, Qiang Dai, Yinghui Deng, Aorui Zhang, Yingzhe Zhang, and Shuliang Zhang (2018). Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling. Water, 10(5), 622

2. Jing Li, George Taylor, David B. Kidner. Accuracy and reliability of map-matched GPS coordinates: the dependence on terrain model resolution and interpolation algorithm. Computers & Geosciences. Volume 31, Issue 2, March 2005, Pages 241-251

3. Xiangfu Kong, Jiawen Yang, Jiandong Qiu, Qin Zhang, Xunlai Chen, Mingjie Wang, Shan Jiang(2022). Post-event flood mapping for road networks using taxi GPS data. Flood Risk Management, Volume 15, Issue 2, June 2022

4. Seth I. Gutman & Stanley G. Benjamin(2001). The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction. GPS solutions 4, 16-24, 1st April 2001

5. J. Rubner, P. Tavan. A Self-Organizing Network for Principal-Component Analysis. Europhysics Letters, Volume 10, Number 7

6. Till Neudecker, Hannes Hartenstein. Network Layer Aspects of Permissionless Blockchains. IEEE Communications Surveys & Tutorials, Volume 21, Issue 1, Firstquarter 2019 Page 838 - 857

7. João Catalao, Giovanni Nico, Ramon Hanssen, Cristina Catita. Merging GPS and Atmospherically Corrected InSAR Data to Map 3-D Terrain Displacement Velocity. IEEE Transactions on Geoscience and Remote Sensing, Volume 49, Issue 6, June 2011, Page 2354 - 2360

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)
ISBN (Print)
978-1-915371-53-9
ISBN (Online)
978-1-915371-54-6
Published Date
25 May 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/5/20230575
Copyright
25 May 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated