Topological Classification of Small and Medium Sized Urban Road Networks - A Case Study of Indian Cities

Recently, India overtook China to become the world's most populous country. A larger part of the Indian population living in small to medium and large towns and cities have been facing serious problems of traffic congestion and vehicular transportation in urban areas. Consequently, urban road and street networks have occupied a core position in the functioning of cities. Therefore, assessment of the topological patterns of road infrastructure is crucial for improving the performance of transportation since the spatial pattern of the current road networks have greatly impacted the urban mobility. This paper attempts to analyze the topological patterns of road networks of small and medium-sized Indian cities in terms of connectivity and coverage measures using graph theory. Cities have been prioritized with respect to population ranging from 20,000 to 0.5 million. As a result, 505 such cities were selected in this study. The road maps of individual cities were split into lines at intersections, which were then converted to network with attribute parameters such as number of edges and vertices, and were subsequently used to compute topological (connectivity and coverage) measures such as Alpha, Beta, Gamma, Grid Tree Pattern (GTP), Eta indices, Network Density (ND), Edge Graph Density (EGD) and Nodal Graph Density (NGD). The study revealed that on an average, only 41% of the small and medium-sized Indian cities have greater connectivity (for example, Alpha > 0.8) and only 5% cities have network density higher than 5 km. This indicates that the road and street networks are not distributed evenly throughout the Indian cities. Furthermore, smaller cities that are located close to/near large metropolitan cities have higher connectivity and coverage, whereas smaller cities placed far away from metropolitan areas have less development in the road transportation systems.