Comparing urban network morphologies: a new living metric and a framework for evaluating procedurally generated city layouts

With the world population increasing, new living areas must be created to accommodate the increased number of people. The designs of most existing cities have a series of well-documented limitations. For example, some cities have serious traffic congestion problems, while others are unsafe. There is a lot of research on methods of improving parts of existing cities, and in many cases the improvement of a city is a constant and ongoing process. However, this research is limited by a few key factors: it is applied to the designs of current cities; it typically focuses on specific, localised issues; and it typically aims to fulfill a single objective, rather than examining the trade-off involved when analysing all aspects of a city at once. Recently, cities such as The Line (Neom) project in Saudi Arabia, and Brasilia and Canberra before it, have been designed and built from scratch. These projects often make bold claims that their designs are “optimal” in some regard. We introduce a novel “living metric” to quantify the degree of hierarchical living structure (a property associated with organically developed cities) in a city’s road network, and validate it by applying it to six real cities. As a proof of concept, we also demonstrate that this and two further metrics - population density (space efficiency) and mean circuity (travel efficiency) - can be applied to hypothetical city designs. To do this, we introduce CitySprout , a novel procedural road network generator, and generate cities of four distinct morphologies, or “grammars”. We study current examples of planned cities, and discuss the fundamental limitations of attempting to optimise cities based only on the underlying road network. We then demonstrate that different urban morphologies perform better at different metrics, highlighting that optimising a road network is inherently metric-dependent and therefore cannot converge on the “optimal” urban form. We find that a Grid structure maximises population density (under a set of clearly defined assumptions about population distribution); an Organic structure exhibits the most hierarchical “living structure”; and a Line structure minimises the required detours for cross-city travel. These differences highlight the trade-off between competing urban objectives.