This article presents a method to uncover universal patterns and similarities in the urban road networks of the 80 most populated cities in the world. To that end, we used degree distribution, link length distribution, and intersection angle distribution as topological and geometric properties of road networks. Moreover, we used ISOMAP, a nonlinear dimension reduction technique, to better express variations across cities, and we used K-means to cluster cities. Overall, we uncovered one universal pattern between the number of nodes and links across all cities and identified five classes of cities. Gridiron Cities tend to have many 90° angles. Long Link Cities have a disproportionately high number of long links and include mostly Chinese cities that developed towards the end of the 20th century. Organic Cities tend to have short links and more non-90 and 180° angles; they also include relatively more historical cities. Hybrid Cities tend to have both short and long links; they include cities that evolved both historically and recently. Finally, Mixed Cities exhibit features from all other classes. These findings can help transport planners and policymakers identify peer cities that share similar characteristics and use their characteristics to craft tailored transport policies.

Making smart and informed decisions often requires the integration and analysis of large amounts of data. However, integrating these data is rarely straightforward, mainly because of heterogeneities in data structure and format. In this study, we focus on two widely used data formats by municipalities to store digital maps of their infrastructure: Computer-Aided Design (CAD) and Geographic Information Systems (GIS). While most municipalities still maintain infrastructure data in CAD format, many have started converting them to GIS since GIS includes geographical coordinates. However, the inherent differences between these two formats pose challenges to accurately converting information from CAD to GIS. The main goal of this study is to develop a procedure to help municipalities to perform CAD-to-GIS conversion. To that end, potential problems in CAD-to-GIS conversion were first identified through interviews with practitioners at different U.S. municipalities and through a literature review. Taken together, we propose the C2G framework to streamline the conversion process while minimizing information loss. The framework consists of five stages, and the execution of this framework and tasks involved in each stage are explained. Moreover, we apply the framework to real-world underground stormwater infrastructure data obtained from the University of Illinois at Chicago (UIC) to illustrate the framework’s applicability. The case study explains details about the technical difficulties we encountered in the process and provides recommendations to circumvent those difficulties. The results from the case study showed that the C2G framework was able to successfully convert CAD data to GIS data. Although the framework is developed specific to the needs of CAD/GIS practitioners in the US municipalities, it can be adopted in most CAD-to-GIS conversion situations. The information learned during the interviews supports the need for a standard CAD-to-GIS conversion process. The contribution of this study is to fill this gap by developing a generalized framework to carry out CAD-to-GIS conversion which only requires basic knowledge of CAD and GIS.