From one-way streets to percolation on random mixed graphs
Vincent Verbavatz, Marc Barthelemy

TL;DR
This paper investigates how one-way streets affect urban traffic patterns and models this effect using a percolation framework on mixed graphs, revealing a phase transition in connectivity that differs from classical percolation.
Contribution
It introduces a novel mixed graph model incorporating one-way streets and analyzes the percolation transition, identifying a new universality class and connecting urban street network effects to statistical physics.
Findings
Empirical one-way street effects induce non-universal detour exponents.
A threshold p_c exists where the strongly connected component vanishes.
The transition exhibits a new universality class distinct from classical percolation.
Abstract
In most studies, street networks are considered as undirected graphs while one-way streets and their effect on shortest paths are usually ignored. Here, we first study the empirical effect of one-way streets in about cities in the world. Their presence induces a detour that persists over a wide range of distances and characterized by a non-universal exponent. The effect of one-ways on the pattern of shortest paths is then twofold: they mitigate local traffic in certain areas but create bottlenecks elsewhere. This empirical study leads naturally to consider a mixed graph model of 2d regular lattices with both undirected links and a diluted variable fraction of randomly directed links which mimics the presence of one-ways in a street network. We study the size of the strongly connected component (SCC) versus and demonstrate the existence of a threshold above which the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
