{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T12:57:24Z","timestamp":1761397044472,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T00:00:00Z","timestamp":1745366400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Social Science Foundation of China","award":["23&ZDA80","1053320230988"],"award-info":[{"award-number":["23&ZDA80","1053320230988"]}]},{"DOI":"10.13039\/501100012476","name":"Fundamental Research Funds for the Central Universities of Central South University","doi-asserted-by":"publisher","award":["23&ZDA80","1053320230988"],"award-info":[{"award-number":["23&ZDA80","1053320230988"]}],"id":[{"id":"10.13039\/501100012476","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Mass shootings result in significant casualties. Due to the complexity of buildings, capturing crowd dynamics during mass shooting incidents is particularly challenging. Therefore, it is necessary to study crowd dynamics and the key mechanisms of mass shooting incidents and explore optimal building design solutions to mitigate the damage caused by terrorist attacks and enhance urban safety. In this study, we focused on the Bataclan Shooting (13 November 2015) as the target case. We used an agent-based model (ABM) to model both the attacking force (shooting) and counterforce (anti-terrorism response). According to the real situation, the dynamic behavior of three types of agents (civilians, police, and shooters) during the shooting accident was modeled to explore the key mechanism of individual behavior. Taking civilian casualties, police deaths, and shooter deaths as the real target values, we obtained combinations for optimal solutions fitting the target values. Under the optimal solutions, we verified the effectiveness and robustness of the model. We also used artificial neural networks (ANNs) to detect the predictive stability of the ABM model\u2019s parameters. In addition, we studied the counterfactual situation to explore the impact of police anti-terrorism strategies and building exits on public safety evacuation. The results show that for the real cases, the optimal anti-terrorism size was four police and the optimal response time was 40 ticks. For double-layer buildings, it was necessary to set exits on each floor, and the uniform distribution of exits was conducive to evacuation under emergencies. These findings can improve police patrol routes and the location of police stations and promote the creation of public safety structures, enhancing the urban emergency response capacity and the level of public safety governance.<\/jats:p>","DOI":"10.3390\/systems13050310","type":"journal-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T10:40:48Z","timestamp":1745404848000},"page":"310","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Crowd Evacuation Dynamics Under Shooting Attacks in Multi-Story Buildings"],"prefix":"10.3390","volume":"13","author":[{"given":"Dianhan","family":"Chen","sequence":"first","affiliation":[{"name":"School of Public Administration, Central South University, Changsha 410083, China"},{"name":"PKU-Wuhan Institute for Artificial Intelligence, Wuhan 430070, China"}]},{"given":"Peng","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Public Administration, Central South University, Changsha 410083, China"},{"name":"PKU-Wuhan Institute for Artificial Intelligence, Wuhan 430070, China"}]},{"given":"Yaping","family":"Niu","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Shaanxi University of Science & Technology, Xi\u2019an 710021, China"}]},{"given":"Pengfei","family":"Lv","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100302","DOI":"10.1016\/j.ssmmh.2024.100302","article-title":"The mental health consequences of interpersonal gun violence: A systematic review","volume":"5","author":"Koya","year":"2024","journal-title":"SSM-Ment. 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