城市轨道交通安检集中判图人员配置研究
付保明1张宁2石琦玉3
Staffing for Centralized Image Interpretation in Urban Rail Transit Security Inspection
FU Baoming1ZHANG Ning2SHI Qiyu3
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作者信息:1.苏州轨道交通建设有限公司， 215004， 苏州
2.东南大学智能运输系统研究中心轨道交通研究所， 210008， 南京
3.上海交通职业技术学院轨道交通学院， 200241， 上海
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Affiliation:1.Suzhou Rail Transit Construction Co., Ltd., 215004, Suzhou, China
2.ITS Rail Transit Research Institute, Southeast University, 210008, Nanjing, China
3.School of Urban Railway Transportation, Shanghai Communications Polytechnic, 200241, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.20230479
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中图分类号/CLCN:U231.92
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栏目/Col:运营管理
摘要:
［目的］城市轨道交通安检集中判图业务模式可显著降低人力成本，提高安检效率，提升安检智慧化水平，但判图人员配置却缺乏相应的标准，需对此开展相应研究，为判图中心的建设提供可靠的指导依据。［方法］介绍了安检集中判图的含义、意义及影响因素；基于排队论，结合安检集中判图的业务流程及车站现场运营管理需求，构建乘客安检排队模型，从而确定集中判图中心坐席的配置需求；结合苏州地铁3号线车站安检点的配置情况，利用安检排队模型，计算出判图平台坐席配置规模。［结果及结论］采用基于排队论的安检集中判图人员配置模型，需在高峰期至少配置7名判图人员，判图坐席数量可降低30%；非高峰期至少配置3名判图人员，判图坐席数量可降低70%。车站安检点的服务时长为18 h时，判图坐席数量的综合降低率为58%，减员效果显著。
Abstracts:
［Objective］ The centralized image interpretation mode in urban rail transit security inspection can significantly reduce labor costs, improve inspection efficiency, and enhance the inspection intelligence level. However, there is a lack of standards for image interpretation staffing, necessitating corresponding research to provide reliable guidance for the image interpretation center construction. ［Method］ The concept, significance, and influencing factors of centralized image interpretation in security inspection are introduced. Based on queuing theory and considering the business process of centralized image interpretation as well as the on-site operational management requirements at stations, a passenger security inspection queuing model is constructed, thus determining the configuration requirements for centralized image interpretation center seats. With reference to the configuration of station security checkpoints on Suzhou Metro Line 3, and utilizing the inspection queuing model, the configuration scale of image interpretation platform is calculated. ［Result & Conclusion］ According to the queue theory-based staffing model for centralized image interpretation, at least 7 image interpreters are needed during peak hours, reducing the number of interpretation post by 30%. During off-peak periods, at least 3 interpreters are needed, achieving a 70% reduction in the number of interpretation post. The service duration of security inspection checkpoints at station is 18 hours, and the overall reduction rate of the interpretation post number is 58%, demonstrating a significant reduction in staffing requirements.
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