智能化民航安保的研究热点与发展趋势

张青松; 魏祥宇; 吴煜

doi:10.3963/j.jssn.1674-4861.2023.05.001

智能化民航安保的研究热点与发展趋势

doi: 10.3963/j.jssn.1674-4861.2023.05.001

张青松^{1, 2, ,},
魏祥宇²,
吴煜²

1.
中国民航大学民航热灾害防控与应急重点实验室天津 300300
2.
中国民航大学安全科学与工程学院天津 300300

基金项目:

国家重点研发计划项目 2016YFC0802601

详细信息

通讯作者:
张青松（1977—），博士，教授. 研究方向：民航安全与应急管理、飞机防火与灭火等. E-mail：nkzqsong@126.com

中图分类号: X949
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- 被引次数: 0
出版历程
- 收稿日期: 2022-09-08
- 网络出版日期: 2024-01-18

A Review of Focus and Development Trends in Intelligent Civil Aviation Security

ZHANG Qingsong^{1, 2
, ,},
WEI Xiangyu²,
WU Yu²

1.
Key Laboratory of Civil Aviation Thermal Hazards Prevention and Emergency Response, Civil Aviation University of China, Tianjin 300300, China
2.
School of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China

摘要

摘要: 随着民用航空运输规模快速增长，智慧民航背景下的民航安保工作逐步转向开放式、全流程的自助服务，日益复杂的安全需求亦决定了传统安保向智能化安保的转变趋势。目前，国内外学者对智能化民航安保展开了大量研究，为系统把握智能化民航安保的研究热点和发展趋势，以中国知网和Web of Science核心集合数据库中1 229篇智能化民航安保研究相关文献为数据源，利用CiteSpace软件，从国家和机构分布、主要期刊来源分布、关键词聚类以及关键词突现等方面进行可视化文献计量分析，总结并探讨该领域的研究热点和发展趋势。研究表明：①1998—2021年，国内外学者对智能化民航安保的研究趋势基本一致，总体发文量呈波动式上涨，自2019年起有所降低；②从国家和机构分布来看，发文量最多的国家为中国和美国，共占比37.04%，欧洲国家在该领域的研究合作更为密切；国内主要研究机构包括中国民航大学、中国民航科学技术研究院、中国民用航空飞行学院等，国外主要研究机构包括荷兰代尔夫特理工大学、美国伊利诺伊大学等；③该领域的热点主题包括民用航空营运安全保卫研究、民用机场安全保卫研究和安全检查研究，其中，仿真技术和网络信息安全是民用航空营运安全保卫的热点研究方向，应急疏散和基于主体的模型（agent-based modeling，ABM）是民用机场安全保卫的热点研究方向，旅客差异化、毫米波安检门、机器学习与现有安检技术结合是安全检查的热点研究方向，我国在智能化民航安保领域经济分析和网络信息安全方面的研究有待加强；④智能识别技术在预警和报警方面的研究、仿真技术结合虚拟现实技术进行安保人员培训或演练的研究值得关注。网络信息安全和安全评价模型的优化是当前智能化民航安保研究的主流趋势。
- 民航安全 /
- 民航安保 /
- 可视化分析 /
- 文献计量学 /
- Cites pace /
- 民用航空
Abstract: With the rapid expansion of civil aviation transportation, aviation security operations within the framework of intelligent civil aviation have shifted towards an open and fully automated self-service process. The increasing complexity of security demands drives the transformation from conventional security practices to intelligent security measures. Currently, both domestic and international scholars have conducted extensive research on intelligent civil aviation security. To systematically analyze the research focus and development trends of intelligent civil aviation security, 1 229 literatures about intelligent civil aviation security from the China National Knowledge Infrastructure (CNKI) and the Web of Science Core Collection databases are studied. Utilizing CiteSpace software, a visualized bibliometric analysis is conducted covering aspects such as country and institution distribution, major journal sources, keyword clustering, and keyword burst detection. The study aims to summarize and explore the research focus and trends within this field. The findings are as follows: ①Between 1998 and 2021, the global research on intelligent civil aviation security exhibited a similar increasing trend, with a fluctuating rise in overall publication volume, which showed a slight decrease since 2019. ② In terms of country and institution distribution, the highest number of publications originated from China and the United States, accounting for 37.04% collectively. European nations displayed closer research collaboration in this field. Prominent domestic research institutions include Civil Aviation University of China, China Academy of Civil Aviation Science and Technology, Civil Aviation Flight University of China, etc. Notable foreign research institutions include Delft University of Technology in the Netherlands and the University of Illinois in the United States, etc. ③ The hot topic in this field include studies on civil aviation operational safety and security, civil airport safety and security, and security inspection. Besides, simulation technology and network information security are hot research directions within civil aviation operational safety and security. Emergency evacuation and agent-based modeling (ABM) emerge as significant research areas within civil airport safety and security. Passenger differentiation, millimeter-wave security gates, and the integration of machine learning with existing security inspection technologies are identified as hot topics in security inspection research. However, China's research in this field of economic analysis and network information security concerning intelligent civil aviation security needs further reinforcement. ④ The significance of research on intelligent identification technology in the early warning and alarm systems is highlighted, as well as the integration of simulation technology with virtual reality for security personnel training or exercises. Additionally, the optimization of network information security and security evaluation models is the current mainstream trend in intelligent civil aviation security research.
- civil aviation safety /
- civil aviation security /
- visual analysis /
- bibliometrics /
- CiteSpace /
- civil aviation

HTML全文

图 1 1998—2021年智能化民航安保文献时序分布

Figure 1. Time-series distribution of intelligent civil aviation security literature from 1998 to 2021

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图 2 国家和机构分布图谱

Figure 2. Mapping of countries and institutions

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图 3 基于CNKI的智能化民航安保研究领域关键词聚类图谱

Figure 3. Key words cluster map intelligent of civil aviation security research field based on CNKI

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图 4 基于Web of Science的智能化民航安保研究领域关键词聚类图谱

Figure 4. Key words cluster map of intelligent civil aviation security research field based on Web of Science

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表 1 1998—2021年Web of Science智能化民航安保领域发文频次前10国家

Table 1. Top 10 countries for frequency of publications in intelligent civil aviation security in Web of Science 1998—2021

排名	国家	首发年份	时间跨度内发文量/篇				发文篇数(占比/%)
排名	国家	首发年份	1998—2005	2006—2010	2011—2015	2016—2021	发文篇数(占比/%)
1	美国	1998	14	39	51	75	179(20.72)
2	中国	1999	1	14	39	87	141(16.32)
3	英国	2000	3	7	18	34	6(7.18)
4	德国	2000	1	13	17	22	53(6.13)
5	意大利	2002	1	6	15	21	43(4.97)
6	印度	2009	0	1	7	28	36(4.17)
7	瑞士	2007	0	9	11	14	34(3.93)
8	波兰	2007	0	3	12	19	34(3.93)
9	西班牙	2007	0	2	6	18	26(3.01)
10	荷兰	2004	1	2	9	12	24(2.78)
发文频次前10国家发文总量			21	96	185	330	63(73.15)

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表 2 1998—2021年Web of Science智能化民航安保领域发文频次前10机构

Table 2. Top 10 institutions for frequency of publications in intelligent civil aviation security in Web of Science 1998—2021

排名	机构名称	首发年份	时间跨度内发文量/篇				发文篇数（占比/%)
排名	机构名称	首发年份	1998—2005	2006—2010	2011—2015	2016—2021	发文篇数（占比/%)
1	荷兰代尔夫特理工大学	2007	1	1	3	11	16(1.85)
2	美国伊利诺伊大学	2000	1	1	5	6	13(1.50)
3	中国民航大学	2008	0	2	4	5	11(1.27)
4	中国民航科学技术研究院	2011	0	0	3	8	11(1.27)
5	中国民用航空飞行学院	2010	0	1	3	5	9(1.04)
6	瑞士西北应用科技大学	2012	0	0	4	5	9(1.04)
7	波兰华沙理工大学	2014	0	0	3	5	8(0.93)
8	北京航空航天大学	2007	0	1	4	3	8(0.93)
9	德国航空太空中心	2008	0	1	0	6	7(0.81)
10	英国克兰菲尔德大学	2010	0	1	3	2	6(0.69)

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表 3 1998—2021年Web of Science智能化民航安保研究相关文献被引频次前10期刊

Table 3. Top 10 cited journals of Web of Science intelligent civil aviation security research 1998—2021

序号	被引频次	中心性	期刊名称
1	69	0.18	Journal of Air Transport Management
2	47	0.07	Expert Systems with Applications
3	41	0.09	IEEE Transactions on Pattern Analysis and Machine Intelligence
4	27	0.12	Safety Science
5	27	0.13	Transportation Research Part C: Emerging Technologies
6	24	0.08	Journal of Transportation Safety & Security
7	24	0.08	Risk Analysis
8	22	0.09	Reliability Engineering & System Safety
9	20	0.07	Transportation Research Part A: Policy and Practice Pattern Recognition
10	20	0.06	Pattern Recognition

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表 4 基于CNKI的智能化民航安保领域相关文献关键词聚类统计

Table 4. Key words clustering statistics of relevant research in the field of intelligent civil aviation security based on CNKI

聚类ID	聚类大小	聚类轮廓(S)	聚类标签	主要关键词
#0	49	0.942	机场安检	大数据; 智能识别系统; 旅客差异化; 金属探测门
#1	35	0.939	民航安保	民航安保; 反恐预警; 恐怖袭击
#2	27	0.954	民航局	空防安全; 民航安全; 民航强国
#3	16	0.912	民用机场	民航机场; 安保工作; 应急疏散
#4	12	0.903	民用航空	民用航空; 航空安全; 安全保卫; 非法干扰
#5	11	0.947	航空运输	航空运输; 全球治理；自动识别
#6	10	0.935	管理体系	管理体系; 风险管理; 安保措施
#7	10	0.927	排队论	智能分析; 线性规划模型; 乘客分组
#8	9	0.943	智能视频分析	智能视频分析; 安防系统集成; 主动预警
注：#1、#2、#4、#5-民用航空营运安全保卫研究；#3、#6-民用机场安全保卫研究；#0、#7、#8-安全检查研究。

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表 5 基于Web of Science的智能化民航安保领域相关文献关键词聚类统计

Table 5. Key words clustering statistics of relevant research in the field of intelligent civil aviation security based on Web of Science

类ID	聚类大小	聚类轮廓(S)	聚类标签	主要关键词
#0	52	0.894	airport security	visual search；x-ray computed tomography；process optimization
#1	30	0.907	machine learning	deep convolutional neural network；parametric statistics
#2	23	0.838	information management	cybersecurity risk; cyber resilience; efficiency
#3	34	0.837	airport terminal	agent-based modeling; airport ground
#4	49	0.912	security guards	simulation technology；training evaluation；human-machine interaction
#5	22	0.835	homeland security	air traffic management; terrorism
#6	11	0.931	aviation security	human factors; fuzzy logic; accident signs
#7	25	0.829	cost benefit	economic analysis; competition; efficiency; duopoly
#8	12	0.955	risk assessment	system reliability; security risk management; risk class
注：#2、#4、#5、#6-民用航空营运安全保卫研究；#3、#7、#8-民用机场安全保卫研究；#0、#1-安全检查研究。

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表 6 智能化民航安保领域研究文献中文关键词突现

Table 6. Chinese burstness key words

关键词	年份	强度	起止年份	1998—2021
民航安全	1998	5.56	1998 2007
劫机事件	1998	2.14	2011 2012
机场安检	1998	7.6	2013 2018
空防安全	1998	2.69	2013 2018
非法干扰	1998	1.88	2013 2017
仿真	2009	2.9	2018 2021
优化	2005	2.49	2018 2019
智能识别	2002	2.72	2019 2021

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表 7 智能化民航安保领域研究文献英文关键词突现

Table 7. English burstness key words

关键词	年份	强度	起止年份	1998—2021
homeland security	1998	3.79	2003 2012
optimization	1998	3.3	2009 2015
aviation security	1998	4.11	2009 2012
risk	1998	2.79	2013 2017
civil aviation	1998	3.44	2014 2015
model	1998	4.07	2018 2021
attack	1998	2.03	2019 2021
passenger	1998	2.36	2019 2021

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参考文献(51)

[1]	冯文刚. 基于深度长短记忆模型的民航安保事件分析[J]. 中国安全科学学报, 2021, 31 (9): 1-7. FENG W G. Research on civil aviation security event analysis based on LSTM model[J]. China Safety Science Journal, 2021, 31 (9): 1-7. (in Chinese)
[2]	姜明. 对构建新型航空安保培训管理体系的探讨[J]. 民航管理, 2021 (7): 81-84. JIANG M. Discussion on building a new aviation security training management system[J]. Civil Aviation Management, 2021 (7): 81-84. (in Chinese)
[3]	熊中敏, 马海宇, 李帅, 等. 知识图谱在海洋领域的应用及前景分析综述[J]. 计算机工程与应用, 2022, 58 (3): 15-33. XIONG Z M, MA H Y, LI S, et al. A review on the application and prospect analysis of knowledge graphs in the marine field[J]. Computer Engineering and Applications, 2022, 58 (3): 15-33. (in Chinese)
[4]	YAN L X, ZENG T, DENG G Y, et al. Development status and hotspot visualized analysis of autonomous vehicles based on CiteSpace[J]. Journal of Advanced Transportation, 2022, 3 (1): 1-15.
[5]	GAO J, WU X, LUO X, et al. Scientometric analysis of safety sign research: 1990-2019[J]. Int J Environ Res Public Health. 2021, 18 (1): 273. doi: 10.3390/ijerph18010273
[6]	李杰, 李平, 谢启苗, 等. 安全疏散研究的科学知识图谱[J]. 中国安全科学学报, 2018, 28 (1): 1-7. LI J, LI P, XIE Q M, et al. Mapping knowledge domains of safety evacuation in China[J]. China Safety Science Journal, 2018, 28 (1): 1-7. (in Chinese)
[7]	谭章禄, 彭胜男. 煤矿安全生产知识图谱分析[J]. 中国安全科学学报, 2019, 29 (4): 133-139. TAN Z L, PENG S N. Analysis of knowledge mapping of coal mine safety production[J]. China Safety Science Journal, 2019, 29 (4): 133-139. (in Chinese)
[8]	万明, 吴倩, 严利鑫, 等. 道路交通安全研究的现状与热点分析[J]. 交通信息与安全, 2022, 40 (2): 11-21, 37. doi: 10.3963/j.jssn.1674-4861.2022.02.002 WAN M, WU Q, YAN L X, et al. Analysis of the current situation and hot spots of road traffic safety research[J]. Journal of Transport Information and Safety, 2022, 40(2): 11-21, 37. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.02.002
[9]	王剑辉, 朱晓波, 夏正洪, 等. 基于知识图谱的国内空中交通管理研究可视化分析[J]. 交通信息与安全, 2019, 37(6): 11-19. doi: 10.3963/j.issn.1674-4861.2019.06.002 WANG J H, ZHU X B, XIA Z H, et al. Visual analysis of domestic air traffic management research based on knowledge graph[J]. Journal of Transport Information and Safety, 2019, 37 (6): 11-19. (in Chinese) doi: 10.3963/j.issn.1674-4861.2019.06.002
[10]	马晓雪, 刘阳, 刘雨. 基于知识图谱的国内外北极航线安全研究进展与比较分析[J]. 交通信息与安全, 2020, 38(1): 1-12. doi: 10.3963/j.jssn.1674-4861.2020.01.001 MA X X, LIU Y, LIU Y. Progress and comparative analysis of domestic and foreign research on Arctic route safety based on knowledge mapping[J]. Journal of Transport Information and Safety, 2020, 38 (1): 1-12. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2020.01.001
[11]	CHEN C M. CiteSpace Ⅱ: detecting and visualizing emerging trends and transient patterns in scientific literature[J]. Journal of the American Society for Information Science and Technology, 2006, 57 (3): 359-377. doi: 10.1002/asi.20317
[12]	CHEN C M. Searching for intellectual turning points: progressive knowledge domain visualization[J]. Proceedings of the National Academy of Sciences, 2004, 101(supl): 5303-5310.
[13]	任翠萍, 吴群琪, 张圣忠, 等. 基于CiteSpace的危险货物运输研究知识图谱分析[J]. 安全与环境学报, 2018, 18(2): 646-652. REN C P, WU Q Q, ZHANG S Z, et al. Knowledge graph analysis of dangerous goods transportation research based on CiteSpace[J]. Journal of Safety and Environment, 2018, 18 (2): 646-652. (in Chinese)
[14]	Aviation Safety Network. Airliner accident statistics 2017[EB/OL]. (2018-01-09)[2022-11-29]. https://aviation-safety.net/index.php.
[15]	中国民用航空局. 2018年民航业发展统计公报[R]. 北京: 中国民用航空局, 2019. Civil Aviation Administration of China. Statistical Bulletin of Civil Aviation Industry Development 2018[R]. Beijing: Civil Aviation Administration of China, 2019. (in Chinese)
[16]	中国民用航空局. 2019年民航业发展统计公报[R]. 北京: 中国民用航空局, 2020. Civil Aviation Administration of China. Statistical Bulletin of Civil Aviation Industry Development 2019[R]. Beijing: Civil Aviation Administration of China, 2020. (in Chinese)
[17]	云小鹏. 基于CNKI和CiteSpace的应急管理研究进展与展望[J]. 中国安全科学学报, 2022, 32 (8): 185-193. YUN X P. Research progress and prospect of emergency management based on CNKI and CiteSpace[J]. China Safety Science Journal, 2022, 32 (8): 185-193. (in Chinese)
[18]	JACOBSON S H, KOBZA J E, NAKAYAMA M K. A sampling procedure to estimate risk probabilities in access-control security systems[J]. European Journal of Operational Research, 2000, 122 (1): 123-132. doi: 10.1016/S0377-2217(99)00047-8
[19]	ZHOU X, ZHAO G. Global liposome research in the period of 1995—2014: a bibliometric analysis[J]. Scientometrics, 2015, 105 (1): 231-248. doi: 10.1007/s11192-015-1659-6
[20]	陈孝慈, 谭章禄, 马琳, 等. 可视化安全管理知识图谱分析[J]. 中国安全科学学报, 2017, 27 (4): 13-18. CHEN X C, TAN Z L, MA L, et al. Knowledge mapping analysis of visual safety management[J]. China Safety Science Journal, 2017, 27 (4): 13-18. (in Chinese)
[21]	徐德生, 杨可, 段玮. 基于CiteSpace的钢铁行业碳排放可视化分析[J]. 环境工程, 2022, 40 (1): 207-215. XU D S, YANG K, DUAN W. Visual analysis of carbon emission in steel industry based on CiteSpace[J]. Environmental Engineering, 2022, 40 (1): 207-215. (in Chinese)
[22]	陈悦, 陈超美, 刘则渊, 等. CiteSpace知识图谱的方法论功能[J]. 科学学研究, 2015, 33 (2): 242-253. CHEN Y, CHEN C M, LIU Z Y, et al. Methodological functions of the CiteSpace knowledge graph[J]. Studies in Science of Science, 2015, 33 (2): 242-253. (in Chinese)
[23]	魏中许, 刘慧娟, 贺元骅. 民航空防安全威胁预警机制创新——基于情报信息融合视角[J]. 中国软科学, 2013 (9): 1-9. WEI Z X, LIU H J, HE Y H. Innovation of early warning mechanism of civil aviation air defense security threat: based on the perspective of information fusion[J]. China Soft Science, 2013 (9): 1-9. (in Chinese)
[24]	魏中许, 贺元骅. 民航空防安全预警机制创新研究: 基于"曝点-态势"威胁评估方法[J]. 天府新论, 2013 (6): 63-66. WEI Z X, HE Y H. Research on innovation of civil aviation air defense security early warning mechanism: Based on "Exposure point and situation" threat assessment method[J]. New Horizons of Tianfu, 2013 (6): 63-66. (in Chinese)
[25]	庄夏, 魏中许, 贺元骅. 基于Web的民航空防安全威胁预警系统研制[J]. 中国民航飞行学院学报, 2013, 24 (1): 8-11. ZHUANG X, WEI Z X, HE Y H. Development of Web-based civil aviation air defense security threat warning system[J]. Journal of Civil Aviation Flight University of China, 2013, 24 (1): 8-11. (in Chinese)
[26]	韩萍, 王杰, 贾云飞, 等. 民航恐怖威胁信息预警系统的设计与实现[J]. 中国民航大学学报, 2017, 35 (5): 36-40. HAN P, WANG J, JIA Y F, et al. Design and implementation of an early warning system for civil aviation terrorist threat information[J]. Journal of Civil Aviation University of China, 2017, 35 (5): 36-40. (in Chinese)
[27]	项寅. 基于改进神经网络的恐怖袭击风险预警系统[J]. 灾害学, 2018, 33 (1): 183-189. XIANG Y. An improved neural network-based early warning system for terrorist attack risk[J]. Journal of Catastrophology, 2018, 33 (1): 183-189. (in Chinese)
[28]	BUTTUSSI F, CHITTARO L. A comparison of procedural safety training in three conditions: virtual reality headset, smartphone, and printed materials[J]. IEEE Transactions on Learning Technologies, 2021, 14 (1): 1-15. doi: 10.1109/TLT.2020.3033766
[29]	周成, 孔超, 居里锴, 等. 虚实结合的机械安全防护培训系统研究[J]. 中国安全科学学报, 2018, 28 (5): 166-171. ZHOU C, KONG C, JU L K, et al. Research on the combination of virtual and real machine safety protection training system[J]. China Safety Science Journal, 2018, 28(5): 166-171. (in Chinese)
[30]	DOMINIK, MALCIK, MARTIN, et al. Anatomy of biometric passports[J]. Journal of Biomedicine & Biotechnology, 2012 (4): 490362.
[31]	LEE A J, JACOBSON S H. Identifying changing aviation threat environments within an adaptive homeland security advisory system[J]. Risk Analysis, 2012, 32 (2): 319-329. doi: 10.1111/j.1539-6924.2010.01656.x
[32]	GALILEO T, MICAELA D. Risk assessment techniques for civil aviation security[J]. Reliability Engineering & System Safety, 2011, 96 (8): 892-899.
[33]	ELMARADY A A, RAHOUMA K. Studying cybersecurity in civil aviation, including developing and applying aviation cybersecurity risk assessment[J]. IEEE Access, 2021, 9: 143997-144016. doi: 10.1109/ACCESS.2021.3121230
[34]	ASHE B, SHIELDS T J. Analysis and modeling of the unannounced evacuation of a large retail store[J]. Fire Mater, 1999, 23 (6): 333-336. doi: 10.1002/(SICI)1099-1018(199911/12)23:6<333::AID-FAM707>3.0.CO;2-2
[35]	张培文, 孙宏, 周杰松. 航站楼出发厅应急疏散仿真[J]. 科学技术与工程, 2017, 17 (35): 156-162. ZHANG P W, SUN H, ZHOU J S. Simulation of emergency evacuation in departure lobby of terminal building[J]. Science Technology and Engineering, 2017, 17(35): 156-162. (in Chinese)
[36]	王珺. XZ机场安检部门航空安保管理问题研究[D]. 郑州: 河南大学, 2017. WANG J. Research on aviation security management of security department in XZ airport[D]. Zhengzhou: Henan University, 2017. (in Chinese)
[37]	MMEKIC A, MOHAMMADI Z S S, SHARPANSKYKH A. Systemic agent-Based modeling and analysis of passenger discretionary activities in airport terminals[J]. Aerospace. 2021, 8 (6): 162-183.
[38]	JANSSENS, SHARPANSKYKHA, CURRANR. Agent-based modelling and analysis of security and efficiency in airport terminals[J]. Transportation Research Part C: Emerging Technologies, 2019, 100 (3): 142-160.
[39]	DING M, DING Y Y, WU X Z, et al. Action recognition of individuals on an airport apron based on tracking bounding boxes of the thermal infrared target[J]. Infrared Physics & Technology, 2021, 117: 103859.
[40]	WILKE S, MAJUMDAR A, OCHIENG W Y. The impact of airport characteristics on airport surface accidents and incidents[J]. Journal of Safety Research, 2015, 53 (6): 63-75.
[41]	杨骁勇, 张辉, 刘尚豫, 等. 航空安全领域研究进展可视化综述[J]. 交通信息与安全, 2021, 39 (3): 8-16. doi: 10.3963/j.jssn.1674-4861.2021.03.002 YANG X Y, ZHANG H, LIU S Y, et al. A visual review of research progress in aviation safety[J]. Journal of Transport Information and Safety, 2021, 39 (3): 8-16. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.03.002
[42]	ALBERT L A, NIKOLAEV A, LEE A J, et al. A review of risk-based security and its impact on TSA PreCheck[J]. ⅡSE Transactions, 2020, 53 (6): 657-670.
[43]	冯文刚, 姜兆菲璠. 基于民航旅客分级分类方法的差异化安检和旅客风险演化研究[J]. 数据分析与知识发现, 2020, 4 (12): 105-119. FENG W G, JIANG Z F P. Research on differentiated security screening and passenger risk evolution based on civil aviation passenger classification method[J]. Data Analysis and Knowledge Discovery, 2020, 4 (12): 105-119. (in Chinese)
[44]	赵振武, 唐百慧, 张沉沉. 机场旅客行李托运差异化安检模式安全性研究[J]. 中国安全生产科学技术, 2021, 17(4): 178-182. ZHAO Z W, TANG B H, ZHANG C C. Research on the safety of differential security screening model for passenger baggage check-in at airports[J]. Journal of Safety Science and Technology, 2021, 17 (4): 178-182. (in Chinese)
[45]	CHERMAK L, BRECKON T P, FLITTON G T, et al. Geometrical approach for automatic detection of liquid surfaces in 3D computed tomography baggage imagery[J]. Journal of Photographic Science, 2015, 63 (8): 447-457.
[46]	WANG Q, ISMAIL K N, BRECKON T P. An approach for adaptive automatic threat recognition within 3D computed tomography images for baggage security screening[J]. Journal of X-Ray Science and Technology, 2020, 28 (1): 35-58.
[47]	TSENG C H, HSIEH C C, JWO D J, et al. Person retrieval in video surveillance using deep learning-based instance segmentation[J]. Hindawi Limited, 2021(2021): 9566628: 1-9566628: 12.
[48]	崔欣, 汪金辉, 李杰. 基于CiteSpace池火研究知识图谱分析[J]. 消防科学与技术, 2019, 38 (11): 1618-1623. CUI X, WANG J H, LI J. Knowledge Map Analysis of pool fire based on CiteSpace[J]. Fire Science and Technology, 2019, 38 (11): 1618-1623. (in Chinese)
[49]	PHAM T Q, HOANG N A, QUACH H L, et al. Timeliness of contact tracing among flight passengers during the COVID-19 epidemic in Vietnam[J]. BMC infectious diseases, 2021, 21 (1): 393.
[50]	YANG H Y, FENG Y H. A Pythagorean fuzzy Petri net based security assessment model for civil aviation airport security inspection information system[J]. International Journal of Intelligent Systems, 2021, 36 (5): 2122-2143.
[51]	ZHAO H L, ZHANG N, GUAN Y. Safety assessment model for dangerous goods transport by air carrier[J]. Sustainability, 2018, 10 (5): 1306.