The paper presents a dual approach to analyzing urban street networks, focusing on their structural and dynamic properties. It introduces the Intersection Continuity Negotiation (ICN) model to construct dual graphs, where streets are nodes and intersections are edges, allowing for a more accurate representation of urban street continuity. The study examines six urban street networks with different patterns and historical backgrounds, comparing their structural properties. The dual graphs reveal that most networks exhibit scale-free properties, characterized by a power-law degree distribution and small-world properties, indicating a high level of connectivity and efficiency. The analysis also highlights differences in clustering coefficients and degree correlations, showing that some networks exhibit disassortative mixing. The results suggest that urban street networks, when represented as dual graphs, display characteristics similar to other complex networks, such as scale-free behavior and small-world properties. The study emphasizes the importance of considering both structural and dynamic aspects of urban networks, providing insights into the organization and efficiency of urban street systems. The findings contribute to the understanding of urban planning and the role of network analysis in modeling urban environments.The paper presents a dual approach to analyzing urban street networks, focusing on their structural and dynamic properties. It introduces the Intersection Continuity Negotiation (ICN) model to construct dual graphs, where streets are nodes and intersections are edges, allowing for a more accurate representation of urban street continuity. The study examines six urban street networks with different patterns and historical backgrounds, comparing their structural properties. The dual graphs reveal that most networks exhibit scale-free properties, characterized by a power-law degree distribution and small-world properties, indicating a high level of connectivity and efficiency. The analysis also highlights differences in clustering coefficients and degree correlations, showing that some networks exhibit disassortative mixing. The results suggest that urban street networks, when represented as dual graphs, display characteristics similar to other complex networks, such as scale-free behavior and small-world properties. The study emphasizes the importance of considering both structural and dynamic aspects of urban networks, providing insights into the organization and efficiency of urban street systems. The findings contribute to the understanding of urban planning and the role of network analysis in modeling urban environments.