An efficient dynamic route optimization for urban flooding evacuation based on Cellular Automata. (May 2021)
- Record Type:
- Journal Article
- Title:
- An efficient dynamic route optimization for urban flooding evacuation based on Cellular Automata. (May 2021)
- Main Title:
- An efficient dynamic route optimization for urban flooding evacuation based on Cellular Automata
- Authors:
- He, Mengnan
Chen, Cheng
Zheng, Feifei
Chen, Qiuwen
Zhang, Jianyun
Yan, Hanlu
Lin, Yuqing - Abstract:
- Abstract: Flooding has been one of the major issues that have seriously hampered the developments of the urban systems, as well as threatened the urban water environments. To mitigate the impacts of floods, it is highly important to identify effective evacuation plans with the aid of computer-based methods. However, effectively identifying the dynamic evacuation route based on the evolution of flooding status is difficult and challenging. To this end, this study develops a Cellular Automata-based Dynamic Route Optimization (CADRO) algorithm to identify the dynamic flood evacuation route (FER), where the hydrodynamics, topography and human response time are incorporated. The proposed CADRO is applied in a suburb of Yangzhou City, China, and results demonstrate the people trapped rate, the mean and maximum length of FERs are shortened by nearly 32.70%, 34.04% and 7.90%, respectively compared with the traditional A* algorithm used for evacuation route optimization. One important feature of the proposed CADRO is that it can identify the dynamical variation of terrain connectivity within the flooding process, thereby offering the optimal FERs. In addition, the impacts of the human response time to the FERs are investigated in this study. It is anticipated that the proposed CADRO can be greatly beneficial to the urban flooding risk management. Highlights: Dynamic route optimization for urban flooding evacuation was proposed. A Cellular Automata-based Dynamic Route OptimizationAbstract: Flooding has been one of the major issues that have seriously hampered the developments of the urban systems, as well as threatened the urban water environments. To mitigate the impacts of floods, it is highly important to identify effective evacuation plans with the aid of computer-based methods. However, effectively identifying the dynamic evacuation route based on the evolution of flooding status is difficult and challenging. To this end, this study develops a Cellular Automata-based Dynamic Route Optimization (CADRO) algorithm to identify the dynamic flood evacuation route (FER), where the hydrodynamics, topography and human response time are incorporated. The proposed CADRO is applied in a suburb of Yangzhou City, China, and results demonstrate the people trapped rate, the mean and maximum length of FERs are shortened by nearly 32.70%, 34.04% and 7.90%, respectively compared with the traditional A* algorithm used for evacuation route optimization. One important feature of the proposed CADRO is that it can identify the dynamical variation of terrain connectivity within the flooding process, thereby offering the optimal FERs. In addition, the impacts of the human response time to the FERs are investigated in this study. It is anticipated that the proposed CADRO can be greatly beneficial to the urban flooding risk management. Highlights: Dynamic route optimization for urban flooding evacuation was proposed. A Cellular Automata-based Dynamic Route Optimization (CADRO) algorithm was built. The CADRO algorithm can largely improve the effectiveness of flood evacuation. People's initial location and response time affect the optimized dynamic evacuation route. … (more)
- Is Part Of:
- Computers, environment and urban systems. Volume 87(2021)
- Journal:
- Computers, environment and urban systems
- Issue:
- Volume 87(2021)
- Issue Display:
- Volume 87, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 87
- Issue:
- 2021
- Issue Sort Value:
- 2021-0087-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05
- Subjects:
- Urban flood -- Dynamic evacuation route -- Cellular automata -- Risk management
City planning -- Data processing -- Periodicals
Regional planning -- Data processing -- Periodicals
303.4834 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01989715 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compenvurbsys.2021.101622 ↗
- Languages:
- English
- ISSNs:
- 0198-9715
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.914000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22546.xml