中文摘要：

城市道路交通网络中个别节点的失效，可能引发大规模的交通瘫痪。为描述这种级联失效行为，考虑节点的自修复功能和灾害蔓延机制，基于复杂网络的蔓延动力学理论构建了城市道路交通网络灾害蔓延动力学模型。利用灾害蔓延动力学模型分析了城市道路交通网络节点失效与节点连接强度、节点度及自修复因子的相关性。结果表明，节点自修复能力和延迟时间因子对灾害蔓延有重要影响，所建立的模型能有效模拟城市道路交通网络的灾害演化动力学行为。

英文摘要：

The present paper is to introduce a dynamics model imitating the disastrous sprawling for cascading failure in urban road traffic network developed by the given author. The model intends to vividly describe the cascading failure behavior of the urban traffic based on the complex network theory, with some failure nodes leading to traffic gridlocks desperately. On the other hand, it can also be believed that the failure nodes in the urban road traffic network should have the ability to self-control and regulate to recover from the spreading disaster. That is to say, the dynamics urban traffic network system enjoys its own self-repairing function determined by its self-repairing factors in spite of its disaster sprawling mechanism very much like the neural network model of human mind. And, in this connection, it would be convenient to define the properties of the traffic nodes on the basis of the saturation degree of the intersection. To be accurate, the node properties of the traffic road system are likely to obey the Sigmoid type functions. And, then, chronologically speaking, the dynamics model can also be defined as time-node evolutional when we depict the disaster spreading dynamics behavior comprehensively in view of the connection strength, while considering the self-repairing factors, its disaster sprawling mechanism, and so on. And, in light of its dynamic evolution nature, the correlations between the node failure and the connection strength, we should also pay attention to its node degrees and its self-repairing factors. Even the node failure can also be understood positively related with the connection strength. Of course, the node degree can also be negatively related with the self-repairing factor. And, finally, a numeric example can be devised to explain the relationship between the disaster sprawling factor and the self-repairing factor, as well as the delay time factor, as is defined by the traffic flow wave theory. The numeric example shows： （1） The time of self-repairing is much longer if se