Loading…
Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model
Running is often accompanied by fear or panic during emergency evacuation, and the evacuation of pedestrian crowds at different speeds poses additional challenges in terms of modeling and simulation. To investigate the fundamental interference of running pedestrians in the evacuation process, in thi...
Saved in:
Published in: | IEEE access 2023, Vol.11, p.138602-138613 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | cdi_FETCH-LOGICAL-c359t-95010955c59313dd605dc292a1b5ce4359b67cb21edc2fcd9f78a79ea09abb253 |
container_end_page | 138613 |
container_issue | |
container_start_page | 138602 |
container_title | IEEE access |
container_volume | 11 |
creator | Yu, Tao Yang, Hai-Dong |
description | Running is often accompanied by fear or panic during emergency evacuation, and the evacuation of pedestrian crowds at different speeds poses additional challenges in terms of modeling and simulation. To investigate the fundamental interference of running pedestrians in the evacuation process, in this study, an extended cellular automata model was developed to simulate the evacuation of mixed groups of walking and running pedestrians in an area with multiple exits. The innovations of this extended model are the application of the dynamic potential field algorithm considering panic propagation, pedestrian running caused by panic, and pedestrian ratio and obstacle layouts. Running pedestrians, converted from walking pedestrians, were recognized by the number of k-nearest neighbors in the moving direction based on the Manhattan distance method. The effects of initial pedestrian density and obstacle layout were studied using numerical simulations. The simulation results indicate that a certain number of running pedestrians are needed to improve the evacuation efficiency, and the panic is contagious to others in that walking pedestrians transform into running pedestrians to accelerate the evacuation speed. The research provides insights for improving pedestrian-evacuation efficiency in facilities similar to the scene used in the experiment. |
doi_str_mv | 10.1109/ACCESS.2023.3336914 |
format | article |
fullrecord | <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_ieee_primary_10347261</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10347261</ieee_id><doaj_id>oai_doaj_org_article_3aeded518dd0431e8cacbd5fb64f2310</doaj_id><sourcerecordid>2902116390</sourcerecordid><originalsourceid>FETCH-LOGICAL-c359t-95010955c59313dd605dc292a1b5ce4359b67cb21edc2fcd9f78a79ea09abb253</originalsourceid><addsrcrecordid>eNpNUV1LxDAQLKKgqL9AHwo-90yyTXvx7aznByiKp89hm2wlR6_RtEX89-asiPuyyzAzOzBJcsLZjHOmzhdVtVytZoIJmAFAoXi-kxwIXqgMJBS7_-795Ljv1yzOPEKyPEgeVm4ztjg436W-SZ_HrnPdW1oF_2nTq68ON870F-mTH6gbHLbZJfZk04raNspCuhgHv8EB0wdvqT1K9hpsezr-3YfJ6_XypbrN7h9v7qrFfWZAqiFTksXgUhqpgIO1BZPWCCWQ19JQHjl1UZpacIpwY6xqyjmWipAprGsh4TC5m3ytx7V-D26D4Ut7dPoH8OFNYxicaUkDkiUr-dxalgOnuUFTW9nURd4I4Cx6nU1e78F_jNQPeu3H0MX4WigmOC9AbVkwsUzwfR-o-fvKmd7WoKca9LYG_VtDVJ1OKkdE_xSQl6Lg8A0TsYNi</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2902116390</pqid></control><display><type>article</type><title>Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model</title><source>IEEE Xplore Open Access Journals</source><creator>Yu, Tao ; Yang, Hai-Dong</creator><creatorcontrib>Yu, Tao ; Yang, Hai-Dong</creatorcontrib><description>Running is often accompanied by fear or panic during emergency evacuation, and the evacuation of pedestrian crowds at different speeds poses additional challenges in terms of modeling and simulation. To investigate the fundamental interference of running pedestrians in the evacuation process, in this study, an extended cellular automata model was developed to simulate the evacuation of mixed groups of walking and running pedestrians in an area with multiple exits. The innovations of this extended model are the application of the dynamic potential field algorithm considering panic propagation, pedestrian running caused by panic, and pedestrian ratio and obstacle layouts. Running pedestrians, converted from walking pedestrians, were recognized by the number of k-nearest neighbors in the moving direction based on the Manhattan distance method. The effects of initial pedestrian density and obstacle layout were studied using numerical simulations. The simulation results indicate that a certain number of running pedestrians are needed to improve the evacuation efficiency, and the panic is contagious to others in that walking pedestrians transform into running pedestrians to accelerate the evacuation speed. The research provides insights for improving pedestrian-evacuation efficiency in facilities similar to the scene used in the experiment.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2023.3336914</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; Automata ; Barriers ; Behavioral sciences ; Cellular automata ; cellular automata model ; Computer simulation ; dynamic potential field ; Evacuation ; Heuristic algorithms ; K-nearest neighbors method ; Layouts ; Legged locomotion ; Mathematical models ; Nearest neighbor methods ; Numerical models ; Panic ; pedestrian conversion ; Pedestrians ; Potential fields ; Probability ; Running ; Running pedestrian flow ; Simulation ; Walking</subject><ispartof>IEEE access, 2023, Vol.11, p.138602-138613</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-95010955c59313dd605dc292a1b5ce4359b67cb21edc2fcd9f78a79ea09abb253</cites><orcidid>0000-0003-3425-3295</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10347261$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,4010,27609,27899,27900,27901,54907</link.rule.ids></links><search><creatorcontrib>Yu, Tao</creatorcontrib><creatorcontrib>Yang, Hai-Dong</creatorcontrib><title>Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model</title><title>IEEE access</title><addtitle>Access</addtitle><description>Running is often accompanied by fear or panic during emergency evacuation, and the evacuation of pedestrian crowds at different speeds poses additional challenges in terms of modeling and simulation. To investigate the fundamental interference of running pedestrians in the evacuation process, in this study, an extended cellular automata model was developed to simulate the evacuation of mixed groups of walking and running pedestrians in an area with multiple exits. The innovations of this extended model are the application of the dynamic potential field algorithm considering panic propagation, pedestrian running caused by panic, and pedestrian ratio and obstacle layouts. Running pedestrians, converted from walking pedestrians, were recognized by the number of k-nearest neighbors in the moving direction based on the Manhattan distance method. The effects of initial pedestrian density and obstacle layout were studied using numerical simulations. The simulation results indicate that a certain number of running pedestrians are needed to improve the evacuation efficiency, and the panic is contagious to others in that walking pedestrians transform into running pedestrians to accelerate the evacuation speed. The research provides insights for improving pedestrian-evacuation efficiency in facilities similar to the scene used in the experiment.</description><subject>Algorithms</subject><subject>Automata</subject><subject>Barriers</subject><subject>Behavioral sciences</subject><subject>Cellular automata</subject><subject>cellular automata model</subject><subject>Computer simulation</subject><subject>dynamic potential field</subject><subject>Evacuation</subject><subject>Heuristic algorithms</subject><subject>K-nearest neighbors method</subject><subject>Layouts</subject><subject>Legged locomotion</subject><subject>Mathematical models</subject><subject>Nearest neighbor methods</subject><subject>Numerical models</subject><subject>Panic</subject><subject>pedestrian conversion</subject><subject>Pedestrians</subject><subject>Potential fields</subject><subject>Probability</subject><subject>Running</subject><subject>Running pedestrian flow</subject><subject>Simulation</subject><subject>Walking</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNUV1LxDAQLKKgqL9AHwo-90yyTXvx7aznByiKp89hm2wlR6_RtEX89-asiPuyyzAzOzBJcsLZjHOmzhdVtVytZoIJmAFAoXi-kxwIXqgMJBS7_-795Ljv1yzOPEKyPEgeVm4ztjg436W-SZ_HrnPdW1oF_2nTq68ON870F-mTH6gbHLbZJfZk04raNspCuhgHv8EB0wdvqT1K9hpsezr-3YfJ6_XypbrN7h9v7qrFfWZAqiFTksXgUhqpgIO1BZPWCCWQ19JQHjl1UZpacIpwY6xqyjmWipAprGsh4TC5m3ytx7V-D26D4Ut7dPoH8OFNYxicaUkDkiUr-dxalgOnuUFTW9nURd4I4Cx6nU1e78F_jNQPeu3H0MX4WigmOC9AbVkwsUzwfR-o-fvKmd7WoKca9LYG_VtDVJ1OKkdE_xSQl6Lg8A0TsYNi</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Yu, Tao</creator><creator>Yang, Hai-Dong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-3425-3295</orcidid></search><sort><creationdate>2023</creationdate><title>Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model</title><author>Yu, Tao ; Yang, Hai-Dong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-95010955c59313dd605dc292a1b5ce4359b67cb21edc2fcd9f78a79ea09abb253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Automata</topic><topic>Barriers</topic><topic>Behavioral sciences</topic><topic>Cellular automata</topic><topic>cellular automata model</topic><topic>Computer simulation</topic><topic>dynamic potential field</topic><topic>Evacuation</topic><topic>Heuristic algorithms</topic><topic>K-nearest neighbors method</topic><topic>Layouts</topic><topic>Legged locomotion</topic><topic>Mathematical models</topic><topic>Nearest neighbor methods</topic><topic>Numerical models</topic><topic>Panic</topic><topic>pedestrian conversion</topic><topic>Pedestrians</topic><topic>Potential fields</topic><topic>Probability</topic><topic>Running</topic><topic>Running pedestrian flow</topic><topic>Simulation</topic><topic>Walking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Tao</creatorcontrib><creatorcontrib>Yang, Hai-Dong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Xplore Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Tao</au><au>Yang, Hai-Dong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2023</date><risdate>2023</risdate><volume>11</volume><spage>138602</spage><epage>138613</epage><pages>138602-138613</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Running is often accompanied by fear or panic during emergency evacuation, and the evacuation of pedestrian crowds at different speeds poses additional challenges in terms of modeling and simulation. To investigate the fundamental interference of running pedestrians in the evacuation process, in this study, an extended cellular automata model was developed to simulate the evacuation of mixed groups of walking and running pedestrians in an area with multiple exits. The innovations of this extended model are the application of the dynamic potential field algorithm considering panic propagation, pedestrian running caused by panic, and pedestrian ratio and obstacle layouts. Running pedestrians, converted from walking pedestrians, were recognized by the number of k-nearest neighbors in the moving direction based on the Manhattan distance method. The effects of initial pedestrian density and obstacle layout were studied using numerical simulations. The simulation results indicate that a certain number of running pedestrians are needed to improve the evacuation efficiency, and the panic is contagious to others in that walking pedestrians transform into running pedestrians to accelerate the evacuation speed. The research provides insights for improving pedestrian-evacuation efficiency in facilities similar to the scene used in the experiment.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2023.3336914</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3425-3295</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2169-3536 |
ispartof | IEEE access, 2023, Vol.11, p.138602-138613 |
issn | 2169-3536 2169-3536 |
language | eng |
recordid | cdi_ieee_primary_10347261 |
source | IEEE Xplore Open Access Journals |
subjects | Algorithms Automata Barriers Behavioral sciences Cellular automata cellular automata model Computer simulation dynamic potential field Evacuation Heuristic algorithms K-nearest neighbors method Layouts Legged locomotion Mathematical models Nearest neighbor methods Numerical models Panic pedestrian conversion Pedestrians Potential fields Probability Running Running pedestrian flow Simulation Walking |
title | Simulation of Running Crowd Dynamics: Potential-Based Cellular Automata Model |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-24T11%3A35%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Simulation%20of%20Running%20Crowd%20Dynamics:%20Potential-Based%20Cellular%20Automata%20Model&rft.jtitle=IEEE%20access&rft.au=Yu,%20Tao&rft.date=2023&rft.volume=11&rft.spage=138602&rft.epage=138613&rft.pages=138602-138613&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2023.3336914&rft_dat=%3Cproquest_ieee_%3E2902116390%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c359t-95010955c59313dd605dc292a1b5ce4359b67cb21edc2fcd9f78a79ea09abb253%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2902116390&rft_id=info:pmid/&rft_ieee_id=10347261&rfr_iscdi=true |