# Morphology of travel routes and the organization of cities

## TL;DR

This study analyzes the shape and patterns of travel routes in 92 major cities to understand how urban structure and socioeconomic factors influence movement, revealing commonalities linked to city size and development stage.

## Contribution

It introduces a new metric, inness, to quantify the directional bias of routes and links route morphology with socioeconomic and infrastructural city characteristics.

## Key findings

- Route morphology shows directional bias influenced by congestion and demand.
- Cities with similar inness patterns cluster by size and development stage.
- Higher socioeconomic development correlates with increased connectivity and road hierarchy diversity.

## Abstract

The city is a complex system that evolves through its inherent social and economic interactions. Mediating the movements of people and resources, urban street networks offer a spatial footprint of these activities; consequently their structural characteristics have been of great interest in the literature. In comparison, relatively limited attention has been devoted to the interplay between street structure and its functional usage, i.e., the movement patterns of people and resources. To address this, we study the shape of 472,040 spatiotemporally optimized travel routes in the 92 most populated cities in the world. The routes are sampled in a geographically unbiased way such that their properties can be mapped on to each city, with their summary statistics capturing mesoscale connectivity patterns representing the complete space of possible movement in cities. The collective morphology of routes exhibits a directional bias that could be described as influenced by the attractive (or repulsive) forces resulting from congestion, accessibility and travel demand that relate to various socioeconomic factors. To capture this feature, we propose a simple metric, inness, that maps this force field. An analysis of the morphological patterns of individual cities reveals structural and socioeconomic commonalities among cities with similar inness patterns, in particular that they cluster into groups that are correlated with their size and putative stage of urban development as measured by a series of socioeconomic and infrastructural indicators. Our results lend weight to the insight that levels of urban socioeconomic development are intrinsically tied to increasing physical connectivity and diversity of road hierarchies.