考虑行程时间的高速公路网脆弱性研究
A Study on the Vulnerability of Expressway Networks Considering Travel Time

为避免突发事件造成路网中的部分节点或路段失去其通行能力，进而影响整个路网的运行效率，保障高速公路网络安全运营，运用复杂网络理论对高速公路网络脆弱性进行研究。首先，在Space-L方法的基础上，构建行程时间加权的高速公路网络拓扑结构，并提出了此加权网络中节点重要度的衡量指标；其次，基于节点与边的相关指标，采用删除法模拟高速公路网络在不同攻击策略下的脆弱性变化；最后，结合山东省区域高速公路网交调数据与高速公路收费数据，研究行程时间加权下的高速公路网脆弱性。实例结果表明：行程时间加权的节点重要度指标能够综合考虑高速公路网的多项指标，更好地体现节点的重要度；在高速公路网络的脆弱性方面，不管是节点攻击还是边攻击，高速公路网络对不同攻击策略都表现出一定的脆弱性；从攻击效果来看，蓄意攻击节点策略中，贪心攻击策略要优于初始攻击策略，并且不论是节点还是边攻击策略下，贪心加权介数的攻击策略都要优于其它攻击策略，使网络表现出更强的脆弱性。
To prevent partial nodes or sections in the road network from losing their traffic capacity due to unexpected events, thus affecting the overall operational efficiency of the network and ensuring the safe operation of the highway network, this study applies complex network theory to research the vulnerability of highway networks. Firstly, based on the Space-L method, a journey time-weighted topological structure of the highway network is constructed, and indicators for measuring the importance of nodes in this weighted network are proposed. Secondly, using node and edge-related indicators, the vulnerability changes of the highway network under different attack strategies are simulated through a deletion method. Lastly, combining regional highway network traffic data and toll data from Shandong Province, the vulnerability of the journey time-weighted highway network is studied. The results show that the journey time-weighted node importance indicators can comprehensively consider multiple indicators of the highway network, better reflecting the importance of nodes. In terms of the vulnerability of the highway network, whether it is node or edge attacks, the highway network shows certain vulnerability to different attack strategies. From the perspective of attack effectiveness, in the intentional node attack strategy, the greedy attack strategy is superior to the initial attack strategy. Moreover, whether under node or edge attack strategies, the greedy weighted betweenness attack strategy outperforms other strategies, revealing a greater vulnerability of the network.