Reza Selim, Ferreira Marta Campos, Machado J J M, Tavares João Manuel R S
Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal.
Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal.
Ann Math Artif Intell. 2022 Sep 29:1-20. doi: 10.1007/s10472-022-09818-x.
Road network studies attracted unprecedented and overwhelming interest in recent years due to the clear relationship between human existence and city evolution. Current studies cover many aspects of a road network, for example, road feature extraction from video/image data, road map generalisation, traffic simulation, optimisation of optimal route finding problems, and traffic state prediction. However, analysing road networks as a complex graph is a field to explore. This study presents comparative studies on the Porto, in Portugal, road network sections, mainly of Matosinhos, Paranhos, and Maia municipalities, regarding degree distributions, clustering coefficients, centrality measures, connected components, k-nearest neighbours, and shortest paths. Further insights into the networks took into account the community structures, page rank, and small-world analysis. The results show that the information exchange efficiency of Matosinhos is 0.8, which is 10 and 12.8% more significant than that of the Maia and Paranhos networks, respectively. Other findings stated are: (1) the studied road networks are very accessible and densely linked; (2) they are small-world in nature, with an average length of the shortest pathways between any two roads of 29.17 units, which as found in the scenario of the Maia road network; and (3) the most critical intersections of the studied network are 'Avenida da Boavista, 4100-119 Porto (latitude: 41.157944, longitude: - 8.629105)', and 'Autoestrada do Norte, Porto (latitude: 41.1687869, longitude: - 8.6400656)', based on the analysis of centrality measures.
由于人类生存与城市发展之间存在明确的关系，道路网络研究在近年来引起了前所未有的广泛关注。当前的研究涵盖了道路网络的许多方面，例如从视频/图像数据中提取道路特征、道路地图概括、交通模拟、最优路径查找问题的优化以及交通状态预测。然而，将道路网络作为一个复杂网络进行分析仍是一个有待探索的领域。本研究对葡萄牙波尔图市主要是马托西纽什、帕拉尼奥斯和马亚市的道路网络路段进行了比较研究，涉及度分布、聚类系数、中心性度量、连通分量、k近邻和最短路径。对这些网络的进一步洞察考虑了社区结构、网页排名和小世界分析。结果表明，马托西纽什的信息交换效率为0.8，分别比马亚和帕拉尼奥斯网络的信息交换效率高出10%和12.8%。其他研究结果如下：（1）所研究的道路网络非常容易到达且连接密集；（2）它们本质上是小世界网络，任意两条道路之间最短路径的平均长度为29.17个单位，这在马亚道路网络的情况中也有发现；（3）根据中心性度量分析，所研究网络中最关键的交叉路口是“波尔图博阿维斯塔大道4100 - 119（纬度：41.157944，经度：-8.629105）”和“波尔图北高速公路（纬度：41.1687869，经度：-8.6400656）”。
