段滢滢, 陆锋(中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101)
The impact of different granularity representations on robustness evaluation of city road network
Duan Yingying, Lu Feng(State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
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.