基于GERT网络的应急救援关键路段识别
发布时间：2018-08-15 18:47
【摘要】：为了及时识别出突发事件下城市道路的关键路段,以构建最短应急救援路径,本文提出了一套完整流程.首先,针对路网在应急条件下的贫信息环境特征,设计一种基于模糊综合评判的行程时间估算方法.然后,考虑救援人员的应急心理和经验选择行为,构建面向广义阻抗的GERT(Graph Evaluation and Review Technique)网络模型.最后,运用Dijkstra算法获得救援路径完成关键路段识别.以成都市某区域实际交通网络为算例进行验证,结果表明:基于2种模糊算子估算路段行程速度,其绝对误差为2.722 km/h,精度较高;与传统关键路段识别方法相比,GERT网络模型能更好地反映行程时间和路段拥挤度对路径选择行为的影响(拟合度80.95%),并将重要度识别技术从路网降低到路径层面,效果良好.
[Abstract]:In order to identify the key sections of urban roads in time to construct the shortest emergency rescue path, this paper presents a set of complete flow chart. Firstly, according to the poor information environment characteristics of road network under emergency condition, a method of travel time estimation based on fuzzy comprehensive evaluation is designed. Then, considering the emergency psychological and experiential selection behavior of rescue workers, a generalized impedance oriented GERT (Graph Evaluation and Review Technique) network model is constructed. Finally, the Dijkstra algorithm is used to obtain the rescue path to complete the key road identification. The actual traffic network in a certain area of Chengdu is taken as an example. The results show that the absolute error is 2.722 km / h and the precision is high. Compared with the traditional key road identification method, the GERT network model can better reflect the impact of travel time and road congestion on the path selection behavior (fit degree 80.95%), and reduce the importance recognition technology from road network to path level, and the effect is good.
【作者单位】： 西南交通大学交通运输与物流学院;
【基金】：国家自然科学基金(51308475) 中央高校基本科研业务费专项资金(SWJTUA0920502051307-03)~~
【分类号】：U491
，
本文编号：2185086
[Abstract]:In order to identify the key sections of urban roads in time to construct the shortest emergency rescue path, this paper presents a set of complete flow chart. Firstly, according to the poor information environment characteristics of road network under emergency condition, a method of travel time estimation based on fuzzy comprehensive evaluation is designed. Then, considering the emergency psychological and experiential selection behavior of rescue workers, a generalized impedance oriented GERT (Graph Evaluation and Review Technique) network model is constructed. Finally, the Dijkstra algorithm is used to obtain the rescue path to complete the key road identification. The actual traffic network in a certain area of Chengdu is taken as an example. The results show that the absolute error is 2.722 km / h and the precision is high. Compared with the traditional key road identification method, the GERT network model can better reflect the impact of travel time and road congestion on the path selection behavior (fit degree 80.95%), and reduce the importance recognition technology from road network to path level, and the effect is good.
【作者单位】： 西南交通大学交通运输与物流学院;
【基金】：国家自然科学基金(51308475) 中央高校基本科研业务费专项资金(SWJTUA0920502051307-03)~~
【分类号】：U491
，
本文编号：2185086
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