[1]张晓莉,郭亚娟,王悦,等.韧性理论视角下城市交通应急无人机固定起降设施布局优化*[J].中国安全生产科学技术,2025,21(12):169-176.[doi:10.11731/j.issn.1673-193x.2025.12.021]
ZHANG Xiaoli,GUO Yajuan,WANG Yue,et al.Optimization of fixed takeoff/landing facility location for urban traffic emergency-response uavs under resilience theory framework[J].Journal of Safety Science and Technology,2025,21(12):169-176.[doi:10.11731/j.issn.1673-193x.2025.12.021]
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韧性理论视角下城市交通应急无人机固定起降设施布局优化*
ZHANG Xiaoli,GUO Yajuan,WANG Yue,et al.Optimization of fixed takeoff/landing facility location for urban traffic emergency-response uavs under resilience theory framework[J].Journal of Safety Science and Technology,2025,21(12):169-176.[doi:10.11731/j.issn.1673-193x.2025.12.021]
《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]
- 卷:
- 21
- 期数:
- 2025年12期
- 页码:
- 169-176
- 栏目:
- 职业安全卫生管理与技术
- 出版日期:
- 2025-12-30
文章信息/Info
- Title:
- Optimization of fixed takeoff/landing facility location for urban traffic emergency-response uavs under resilience theory framework
- 文章编号:
- 1673-193X(2025)-12-0169-08
- Keywords:
- resilience theory; takeoff and landing facility layout; NSGA-Ⅱ; emergency-response UAV; traffic incidents
- 分类号:
- X913
- 文献标志码:
- A
- 摘要:
- 为提升城市交通系统在突发事件中的应急响应能力与韧性能级，基于道路网络拓扑结构、运行状态及事故信息等多源异构数据，辨识交通应急需求点，采用K-means聚类分析其空间集聚关系，确定无人机起降设施备选点集合，从健壮性、冗余性和快速性3个维度建立全生命周期韧性评估指标体系，进而构建以韧性效率最大化和综合成本最小化的多目标选址优化模型，并结合非支配排序遗传算法进行求解。研究结果表明：相较单一成本模型，多目标模型仅增加2个设施布设点，覆盖率可提升5.4%且韧性指标可提升26.6%；相较单一韧性模型，在成本减少12.6%的情况下，韧性效能仅下降6.2%；在不同应急需求规模下，选址方案综合效益波动幅度小于5%，验证了模型的良好适应性与稳定性。研究结果可为智慧城市无人机新型基础设施网络优化提供参考。
- Abstract:
- In order to enhance the emergency response capability and resilience level of urban transportation systems under emergencies,this study identifies traffic emergency demand points based on multi-source heterogeneous data,including road network topology,operating status and incident information.K-means clustering is used to analyze their spatial agglomeration patterns and to determine a candidate set of UAV takeoff and landing facility sites.A full life-cycle resilience evaluation index system is then established from three dimensions,namely robustness,redundancy and rapidity.On this basis,a multi-objective site selection optimization model is developed with the objectives of maximizing resilience efficiency and minimizing total cost,and the model is solved using the non-dominated sorting genetic algorithm.The results show that,compared with a cost-only model,the multi-objective model adds only two facility sites,while improving the coverage rate by 5.4% and the resilience index by 26.6%.Compared with a resilience-only model,the proposed model reduces cost by 12.6% with only a 6.2% decrease in resilience performance.Under different scales of emergency demand,the comprehensive benefit of the site selection solution varies by less than 5%,which verifies the good adaptability and stability of the model.The findings can provide a reference for optimizing UAV-based new infrastructure networks in smart cities.
参考文献/References:
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相似文献/References:
备注/Memo
- 备注/Memo:
-
收稿日期： 2025-07-09
* 基金项目： 山东省自然科学基金项目(ZR2021QF110)；济南市高校院所自主培养创新团队项目(202333040)
作者简介： 张晓莉，硕士研究生，主要研究方向为智能交通。
通信作者： 郭亚娟，博士，副教授，主要研究方向为交通数据分析、低空基础设施布局规划。
