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引用本文:耿彦斌,韦献兰.????????????????????????????[J].交通运输系统工程与信息,2010,10(4):131-136.
作者姓名:耿彦斌  韦献兰
作者单位:1.??????? ?滮?о???????? 100028??2.?????л?????????????????? ; ???? 518128
基金项目:国家高技术研究发展计划(863计划)项目 
摘    要:本文着重研究应急交通需求时空分布预测方法. 从分析应急交通需求特点入手,在总结现有研究的基础上,提出广义S型行为反应曲线的概念,并紧扣不同集结点的疏散时间要求和反应参数各异的特点,建立了广义S型需求加载曲线模型,同时给出了单位时段疏散百分比的分析方法. 应用上述方法,设计了分时段应急交通OD需求矩阵的求解算法,从而建立应急交通需求时空分布模型. 基于MATLAB软件对模型编程实现,在对给定算例进行应用后,证明模型能够准确刻画不同时刻的各集结点和整个系统的应急需求疏散比例的动态变化,并有效应用于应急交通时变需求分布的预测.

关 键 词:?????????  ??????  ???????  ??????  ???  S???????  
收稿时间:2010-1-11
修稿时间:2010-4-10

Time-Varying Evacuation Demand Forecasting Model for Emergency Traffic with Multiple Assembly Locations
GENG Yan-bin,WEI Xian-lan.Time-Varying Evacuation Demand Forecasting Model for Emergency Traffic with Multiple Assembly Locations[J].Transportation Systems Engineering and Information,2010,10(4):131-136.
Authors:GENG Yan-bin  WEI Xian-lan
Institution:1.Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China; ??2.Shenzhen Airport (Group) Co., Ltd, Shenzhen 518128, China
Abstract:This paper focuses on the method to forecast time-varying emergency traffic demand distribution. With analyzing the characteristics of emergency traffic demand, through a synthesis of existing relative references, it proposes the generalized S-curve concept for behavioral responses. Subsequently, according to the characteristics of the different evacuation time limit requirements and reaction parameters of each assembly location, a generalized S-type behavioral response curve analysis model is presented, while, the calculation method of evacuation time curve in unit-period is designed. Furthermore, by applying the above-mentioned methods, the algorithm for calculating the emergency traffic OD demand matrix in different period is presented to develop the time-varying emergency traffic demand distribution model. Finally, after a MATLAB-based software model is programmed, the test on the given example demonstrates that the proposed models accurately illustrate the dynamic changes of the emergency demands evacuation percentages in each period for all assembly locations and the entire system. It can also be applied to effectively forecast the time-varying emergency traffic demand distribution.
Keywords:integrated transportation  traffic emergency  time-varying demand  distribution forecasting  evacuation  S-curve
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