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在城市道路网络的基础上,探讨了应用复杂网络理论的可行性和有效性。运用Dijkstra最短路径算法和Space L方法建立初始拓扑网络,并建立了节点度、边度和节点路阻的特性指标模型。在反映路网功能真实性的前提下,优化了拓扑网络,并以某市中心城区道路交通数据为例进行实例分析。分析结果表明:在初始网络中,节点度数的均值为2.850 0,标准差为0.670 8;节点路阻的平均值为84.680 0s,标准差为11.768 8s;在优化网络中,节点度数的均值为38.750 0,标准差为24.683 0,节点路阻的平均值为91.780 0s,标准差为18.862 8s;东西向边的平均度数为42.00,南北向边的平均度数为29.86,内部边的平均度数为55.00,外部边的平均度数为28.33。在优化网络中,当度数较大的节点在路网中失稳时,在非拥挤状态下,最短路径路阻增大,而在拥挤状态下,网络会瘫痪。度数较大的节点与真实路网中交叉口重要程度相符,能够体现交叉口重要程度的差异性。
Based on the urban road network, the feasibility and effectiveness of applying complex network theory are discussed. The initial topology network is established by using Dijkstra shortest path algorithm and Space L method, and the characteristic index model of node degree, edge degree and node resistance is established. On the premise of reflecting the authenticity of the function of the road network, the topology network is optimized, and an example is given in the case of road traffic data of a downtown area. The results show that: in the initial network, the mean of node degree is 2.850 0 and the standard deviation is 0.670 8; the average value of node resistance is 84.680 0s and the standard deviation is 11.768 8s; in the optimized network, the mean of node degree is 38.750 0, the standard deviation is 24.683 0, the average resistance of nodes is 91.780 0s, the standard deviation is 18.862 8s; the average degree of east-west side is 42.00, the average degree of south-north direction is 29.86, the average degree of inner side is 55.00, The average degree of external edges is 28.33. In the optimized network, when the nodes with large degrees of instability are unstable in the road network, the shortest path resistance increases in non-crowded state, while in crowded state, the network will be paralyzed. The nodes with larger degrees coincide with the degree of importance of the intersections in the real road network, which can reflect the difference in importance of intersections.