The ubiquitous efficiency of going further: how street networks affect travel speed

TL;DR

This study reveals a universal nonlinear relationship between travel time and distance in cities, showing that longer trips tend to be more efficient due to street network patterns that minimize deceleration points.

Contribution

The paper uncovers a ubiquitous super-linear scaling law in urban travel trajectories and links it to street network morphology affecting travel efficiency.

Findings

Most cities exhibit a super-linear time-distance relationship with β>1.

Cities with more continuous, large street segments enable faster long-distance travel.

Street network design significantly influences overall travel efficiency.

Abstract

As cities struggle to adapt to more ``people-centered'' urbanism, transportation planning and engineering must innovate to expand the street network strategically in order to ensure efficiency but also to deter sprawl. Here, we conducted a study of over 200 cities around the world to understand the impact that the patterns of deceleration points in streets due to traffic signs has in trajectories done from motorized vehicles. We demonstrate that there is a ubiquitous nonlinear relationship between time and distance in the optimal trajectories within each city. More precisely, given a specific period of time $\tau$, without any traffic, one can move on average up to the distance $\left \langle D \right \rangle \sim\tau^\beta$. We found a super-linear relationship for almost all cities in which $\beta>1.0$. This points to an efficiency of scale when traveling large distances, meaning the average speed will be higher for longer trips when compared to shorter trips. We demonstrate that this efficiency is a consequence of the spatial distribution of large segments of streets without deceleration points, favoring access to routes in which a vehicle can cross large distances without stops. These findings show that cities must consider how their street morphology can affect travel speed.