突发拥挤条件下城市道路网脆弱性识别

发布时间：2018-01-11 02:05

本文关键词：突发拥挤条件下城市道路网脆弱性识别　出处：《公路交通科技》2017年05期 　论文类型：期刊论文

【摘要】：为了量化突发拥挤导致的城市路网的脆弱性变化,首先采用原始法对路网进行了拓扑,选取连通度与网络效率等路网特性指标从中观层面完成了路网的鲁棒性分析,进而生成了对路网鲁棒性有显著影响的改进路网。然后考虑改进路网中突发拥挤路段的排队容量限制,以路网总阻抗变化量为脆弱性识别指标,构建了含通过能力约束的交通网络配流模型。最后设计了Lagrange乘子算法并进行了算例验证。结果表明:基于脆弱性指标的模型能有效识别路网脆弱性,而突发拥挤导致的路段失效将直接导致路网总阻抗的变化并影响整个路网的鲁棒性;与无约束条件下完成的网络配流结果相比,该模型降低了对城市路网络脆弱路段误判的可能性,效果良好。
[Abstract]:In order to quantify the vulnerability change of urban road network caused by sudden congestion, the topology of the road network is first adopted by the original method. Select connectivity and network efficiency and other road network performance indicators from the meso-level to complete the robustness analysis of the road network. Then the improved road network which has a significant impact on the robustness of the road network is generated. Then the queue capacity limit of the sudden congested sections in the road network is considered and the change of the total impedance of the road network is taken as the vulnerability identification index. A traffic network assignment model with capacity constraints is constructed. Finally, the Lagrange multiplier algorithm is designed and verified by an example. The results show that:. The model based on vulnerability index can effectively identify the vulnerability of road network. The failure of the road caused by sudden congestion will directly lead to the change of the total impedance of the road network and affect the robustness of the whole road network. Compared with the results of network assignment under unconstrained conditions, the model reduces the possibility of misjudgment of fragile sections of urban road network, 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】：国家自然科学基金项目(51308475) 中央高校基本科研业务费专项资金项目(SWJTUA0920502051307-03)
【分类号】：U491.13
【正文快照】： 0引言城市路网的突发事件(自然灾害、交通事故,节日游行等)具有成因复杂、涉及面广和高度不确定性等特点。该类事件造成的道路拥挤常使得车辆在路段上排队溢出的可能性更大,交叉口更容易出现连锁拥挤,进而造成大面积路网堵塞。为了应对突发事件导致的路网局部失效,降低突发拥

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