Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulner...Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.展开更多
As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path pla...As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.展开更多
以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形...以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。展开更多
基金supported by the fundings from 2024 Young Talents Program for Science and Technology Thinking Tanks(No.XMSB20240711041)2024 Student Research Program on Dynamic Simulation and Force-on-Force Exercise of Nuclear Security in 3D Interactive Environment Using Reinforcement Learning,Natural Science Foundation of Top Talent of SZTU(No.GDRC202407)+2 种基金Shenzhen Science and Technology Program(No.KCXFZ20240903092603005)Shenzhen Science and Technology Program(No.JCYJ20241202124703004)Shenzhen Science and Technology Program(No.KJZD20230923114117032)。
文摘Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.
基金supported by National Natural Science Foundation of China(No.62073212)Shanghai Science and Technology Commission(No.23ZR1426600).
文摘As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.
文摘以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。
