An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model
Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling....
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhao, Yuan [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Applied intelligence - Springer US, 1991, 51(2020), 1 vom: 06. Aug., Seite 100-123 |
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volume:51 ; year:2020 ; number:1 ; day:06 ; month:08 ; pages:100-123 |
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10.1007/s10489-020-01711-6 |
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| 520 | |a Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. | ||
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10.1007/s10489-020-01711-6 doi (DE-627)OLC2122314621 (DE-He213)s10489-020-01711-6-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yuan verfasserin aut An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. Artificial bee colony algorithm Crowd evacuation Computer simulation Swarm intelligence algorithm Liu, Hong aut Gao, Kaizhou aut Enthalten in Applied intelligence Springer US, 1991 51(2020), 1 vom: 06. Aug., Seite 100-123 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:51 year:2020 number:1 day:06 month:08 pages:100-123 https://doi.org/10.1007/s10489-020-01711-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 51 2020 1 06 08 100-123 |
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10.1007/s10489-020-01711-6 doi (DE-627)OLC2122314621 (DE-He213)s10489-020-01711-6-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yuan verfasserin aut An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. Artificial bee colony algorithm Crowd evacuation Computer simulation Swarm intelligence algorithm Liu, Hong aut Gao, Kaizhou aut Enthalten in Applied intelligence Springer US, 1991 51(2020), 1 vom: 06. Aug., Seite 100-123 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:51 year:2020 number:1 day:06 month:08 pages:100-123 https://doi.org/10.1007/s10489-020-01711-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 51 2020 1 06 08 100-123 |
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10.1007/s10489-020-01711-6 doi (DE-627)OLC2122314621 (DE-He213)s10489-020-01711-6-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yuan verfasserin aut An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. Artificial bee colony algorithm Crowd evacuation Computer simulation Swarm intelligence algorithm Liu, Hong aut Gao, Kaizhou aut Enthalten in Applied intelligence Springer US, 1991 51(2020), 1 vom: 06. Aug., Seite 100-123 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:51 year:2020 number:1 day:06 month:08 pages:100-123 https://doi.org/10.1007/s10489-020-01711-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 51 2020 1 06 08 100-123 |
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10.1007/s10489-020-01711-6 doi (DE-627)OLC2122314621 (DE-He213)s10489-020-01711-6-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yuan verfasserin aut An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. Artificial bee colony algorithm Crowd evacuation Computer simulation Swarm intelligence algorithm Liu, Hong aut Gao, Kaizhou aut Enthalten in Applied intelligence Springer US, 1991 51(2020), 1 vom: 06. Aug., Seite 100-123 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:51 year:2020 number:1 day:06 month:08 pages:100-123 https://doi.org/10.1007/s10489-020-01711-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 51 2020 1 06 08 100-123 |
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10.1007/s10489-020-01711-6 doi (DE-627)OLC2122314621 (DE-He213)s10489-020-01711-6-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yuan verfasserin aut An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. Artificial bee colony algorithm Crowd evacuation Computer simulation Swarm intelligence algorithm Liu, Hong aut Gao, Kaizhou aut Enthalten in Applied intelligence Springer US, 1991 51(2020), 1 vom: 06. Aug., Seite 100-123 (DE-627)130990515 (DE-600)1080229-0 (DE-576)029154286 0924-669X nnns volume:51 year:2020 number:1 day:06 month:08 pages:100-123 https://doi.org/10.1007/s10489-020-01711-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 51 2020 1 06 08 100-123 |
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Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
| abstractGer |
Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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Abstract Simulation modeling is an important tool for simulating crowd behavior and studying the law of crowd evacuation. It is of great significance for exploring evacuation management methods in emergency situations. The real-time change of evacuation is the main challenge of simulation modeling. In the evacuation simulation, it is difficult for people to choose a suitable route according to the change of evacuation dynamics. This paper proposes a new evacuation simulation method which combines an improved artificial bee colony algorithm for dynamic path planning and SFM (Social Force Model) for simulating the movement of pedestrians, to providing pedestrians with timely route selection. In the path planning layer, we developed a MABCM (Multiple-subpopulations Artificial Bee Colony with Memory) algorithm and proposed a new exit evaluation strategy. These methods can plan a route with the shortest evacuation time for pedestrians according to the dynamic changes of evacuation and improve evacuation efficiency. In the simulated motion layer, we use the SFM to avoid collisions and achieve the reproduction of the evacuation scene. We verified the performance of the proposed MABCM on the CEC 2014 benchmark suite, and the results show that it is superior to the four existing artificial bee colony algorithms in most cases. The proposed crowd evacuation method is verified on an existing SFM platform. The experimental results indicate that the proposed method can efficiently evacuate a dense crowd in multiple scenes and can effectively shorten evacuation time. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model |
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Liu, Hong Gao, Kaizhou |
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