Extreme disasters such as earthquakes can cause severe damage to active distribution networks (ADN) and transportation networks. These disasters can lead to road damage, congestion, and large-scale power outage, which makes it difficult to restore power supply to the power grid. In this study, an ADN dynamic collaborative recovery strategy is proposed based on the characteristics of the traffic network and ADN after an earthquake. The proposed strategy integrates finite source and load resources, network reconstruction, and rush repair scheduling. First, a joint disaster damage model of roads and lines of the transportation network was constructed based on the relationship between the transportation network and ADN that is difficult to separate and map to each other after the earthquake. A model of the traffic rush repair travel time of the transportation network was established considering the comprehensive influence of the traffic capacity and traffic flow, and the ADN resilience index combining the time demand and load importance. Second, an ADN hierarchical dynamic cooperative restoration optimization model reflecting the post-earthquake traffic network conditions was established. The outer layer was targeted at determining the maximum resilience index and minimum total emergency repair time, whereas the inner layer was targeted at minimizing economic losses and weighted switch operation times. Third, the improved grey wolf optimization algorithm was used to solve the proposed model, and resources such as multi-type power generation, emergency demand response load, network reconstruction and emergency repair team were coordinated and optimized to improve the resilience of ADNs after earthquakes. Finally, the feasibility and effectiveness of the proposed strategy are verified using an example analysis of the earthquake damage scenario.