城市道路网络结构的健壮性评价需要定量化分析不同类型攻击对路网结构的影响。然而,城市路网拓扑结构在不同表达粒度下具有不同特征,对各种类型攻击的敏感性也存在差异。本文对城市道路网络进行不同表达粒度下的对偶图建模,并借鉴复杂网络中基于网络结构特征刻画的持续性模拟攻击方法,通过观测随机攻击和目的性攻击过程中城市路网结构的变化过程,评估不同表达粒度对城市路网结构健壮性评价的影响。研究选择了6个不同空间形态的城市路网作为实验路网。结果表明,在相同表达粒度下,对于随机攻击或目的性攻击,不同形态的城市路网结构变化过程具有相似特征,但同一城市路网在不同表达粒度下,受到攻击时的结构演变特征有较大差异。因此面向不同应用时需要选择合适的表达粒度来评价路网健壮性。路段粒度适用于评价点状事件造成的交通中断对路网的影响,可以为突发事故应急方案的制定提供依据;路链粒度适用于评价线状事件如整条道路交通管制或改为单行线时对路网的影响,可以辅助交通管理部门制定合理的交通管制方案;社区粒度适用于评价影响范围较大的交通事件如大型文体活动等面状事件对城市交通的影响,同时该表达粒度顾及了道路交通的区域联动,更适用于动态交通环境下的路网健壮性评价。

Robustness analysis of city road networks requires the evaluation of structural change in networks under attacks. The difficulty of robustness analysis is that when modeled at different granularities city road network structures have different characteristics and show different sensitivities to various attacks. In this article, a city road network is first modeled as dual graph at three different granularities. Then, a series of successive simulated attacks are designed based on network structure characterization methods from complex network theory. The robustness analysis is carried out by characterizing the structural change of a city road network under these successive simulated attacks. Six world cities with different urban morphology forms are tested. The results show that at the same granularity, the performances of different city road network under attacks are similar. However, at different granularities, a city road network has quite different performance. Thus, it is important to choose appropriate representation granularity when conducting robustness analysis of city road network for a specific application. We argue that road network represented by segment is suitable for the evaluation on how traffic interruption at certain point affects the network and can provide suggestion on related emergency response. Road network represented by stroke is a good option when we want to evaluate how filiform traffic interruption affects the network and can help to decide traffic control strategies. Road network represented by community is more suitable for robustness analysis under the condition of big events that affect the traffic in a larger area. Moreover, community is an appropriate representation for robustness analysis in dynamic traffic environment since the zonal road traffic interactions could be taken into account.