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.
In order to timely indentify critical road link of urban network in emergencies to establish the shortest emergency rescue path. This paper designs a complete process. Firstly, considering poor information environment of road network under emergency conditions, a method of estimating travel time is presented based on fuzzy comprehensive evaluation. Then, a GERT model is established based on generalized impedance in connection with emergency psychology and empirical selection behavior. Finally, Dijkstra algorithm is used to obtain rescue path and finish critical road links identification. The paper selects an actual traffic network of a region in Chengdu City to verify model and algorithm. The results show that：compared with traditional identify method, GERT network model can reflect the effect of travel time and road link congestion on path choice behavior better （fitting degree is 80.95%）, and makes road link importance identification concreted from network level to path level, which has well effect.
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2017年第4期166-172,共7页
Journal of Transportation Systems Engineering and Information Technology
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)~~
关键词
交通工程
关键路段识别
GERT网络
救援路径
贫信息
模糊数学
traffic engineering
critical link identification
GERT network
rescue path
poor information
fuzzy mathematics
