# Identification of Critical Road Links Based on Static and Dynamic Features [PERSON]
## 1 Introduction  
The phenomenon of urbanization has led to a surge in travel demand in urban areas, which poses a significant challenge to urban traffic. However, the infrastructure development in these areas is constrained by the limitations of urban land, resulting in an inability to meet the changing traffic demand. Traffic congestion is emerging as a major urban problem, posing various challenges in terms of environmental pollution, time wastage, and reduced productivity. The urban traffic network is a time-varying, directed, and weighted network that should account for both its topological structure and travel characteristics. Given the vast size of the urban traffic network, it is not feasible to manage each road link during traffic control. Due to resource and funding limitations, we can only manage a limited number of urban road links. Therefore, it is crucial to determine which road links should be controlled to maintain the normal operation of urban traffic. Additionally, in the event of natural disasters, it is necessary to prioritize which road links to restore or control first to improve the operational efficiency of the urban traffic network. By evaluating the importance of urban road links, we can identify critical road links in the city and prioritize their control and maintenance to ensure the smooth operation of the urban traffic network. The urban road network serves as the foundation of the urban transportation system and is a crucial component of transportation infrastructure. Research [1] indicates that acascading failure phenomenon exists in urban road networks, whereby the failure of a few links can lead to the failure of other links and ultimately affect the efficiency of surrounding local networks. Critical links refer to those links that, when failed due to traffic congestion or accidents, have a significant impact on network operating efficiency. Therefore, it is imperative to identify such critical links and devise management strategies to address the issue of traffic congestion and ensure transportation efficiency. Evaluating the importance of links in the traffic network is significant to solving this problem. By analyzing urban road network topology and traffic data to identify bottlenecks and congestion hotspots, urban traffic management can focus their efforts on the most critical links in the network. This targeted approach can improve traffic flow and reduce congestion, ultimately leading to a more efficient and sustainable transportation system. In the traffic system, traffic travel has been widely linked to the urban spatial structure, and the connection has been extended to the field of urban science theory by many researchers. Some researchers have explored the urban operation mechanism and analyzed the causes of traffic congestion [2] by using large-scale spatio-temporal data. Their analysis involves identifying urban activity hotspot areas [3], urban spatial density [4], and urban spatial structure [5]. Meanwhile, some researchers have combined complex network theory and traffic travel characteristics to explain traffic phenomena. They use quantitative indicators commonly used in complex networks and graph theory, such as degree, centrality, and network efficiency, and analyze the relationship between these indicators and traffic travel to measure the importance of links in the traffic network [6; 7]. Such research efforts can provide valuable insights into the urban traffic phenomenon and pave the way for the development of effective traffic management strategies. In this study, we propose a traffic link importance evaluation method based on combining road network topology with traffic demand and traffic state through network representation learning. Firstly, we establish a directed dual traffic network model using the dual mapping method based on a directed road network, where road links are represented as nodes and the connection relationships between them as edges.