Various unconventional emergencies like natural disasters, public health incidents, accidental disasters and social security emergencies may occur frequently. Emergency evacuation management has been widely used as a crucial strategy to protect human life and property against various disasters and catastrophic events, and is also a prerequisite and basis for the successful implementation of emergency management. This project is to explore scientific problems on unconventional large-scale regional emergency evacuation, using cell transmission model, dynamic traffic assignment and network optimization technology etc. combined with management science, decision theory, behavioral science, etc. Analysis of the variability and vulnerability of the transportation system in disaster zones, and exploration of the behavioral mechanism and psychological characteristics of the affected population are done in an attempt to predict the spatial-temporal evolution of traffic flow in the state of emergency. On the basis of determination of evacuation zones, estimation of evacuation demand and evacuation behaviour analysis, large-scale emergency evacuation models are proposed and the corresponding effective algorithms are designed, aiming at the best configuration of various evacuation strategies, minimizing the network clearance time and improving the evacuation efficiency. This project will provide a theoretical basis and practical support for unconventional large-scale regional emergency evacuation.
各种重大自然灾害、公共卫生事件、事故灾难、社会安全事件等非常规突发事件频繁发生,应急疏散管理是应对突发事件、防止和减少人类生命和财产损失的重要措施,也是应急管理的前提和基础。本项目就是提炼非常规突发事件下大范围区域应急疏散科学问题,运用元胞传输模型、动态交通分配理论以及网络优化技术等工具,结合管理科学、决策理论、行为科学等相关知识,分析受灾区域交通系统的时变性和脆弱性,揭示受灾人群疏散行为机理和心理结构特征,预测应急状态下交通流的时空演化规律,合理划定疏散区域、估计疏散需求,刻画紧急疏散中的交通行为,建立大规模区域应急疏散模型并设计求解算法,寻求各种疏散策略的最佳配置,最大限度地减少疏散路网清空时间、提高疏散效率。本项目将为非常规突事件下大规模区域应急疏散管理提供理论依据和实践支持。
本项目结合管理科学、决策理论、行为科学等相关知识,运用交通流理论、元胞传输模型、网络优化、交通信号优化、系统仿真等技术,研究了基于神经网络的交通量预测、交通状态判别、交通瓶颈模型、一般系统最优交通分配模型、路口和匝道交通信号控制以及应急疏散与应急资源调度问题,并设计了应急系统。该系统可生成应急疏散资源配置方案,实现道路交通安全应急管理、应急资源配置、人群应急疏散功能。本项目将为非常规突事件下大规模区域应急疏散管理提供理论依据和实践支持。
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数据更新时间:2023-05-31
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