Shape and Performance of Fastest Paths over Networks with Interacting Selfish Agents
Marco Cogoni, Giovanni Busonera, and Enrico Gobbetti

TL;DR
This paper analyzes how fastest paths in transportation networks evolve under increasing congestion, focusing on their shape, performance, and the transition to traffic congestion across eight major cities.
Contribution
It introduces a path-based analysis of congestion effects, characterizes the transition to congestion, and identifies critical traffic levels affecting path shape and performance.
Findings
Peak detour and inness near critical traffic levels
Paths attracted to city centers under light traffic, repelled after congestion
Asymmetric performance degradation depending on origin or destination
Abstract
We study the evolution of the fastest paths (FP) in transportation networks under increasing congestion. Moving from the common edge-based to a path-based analysis, we examine the directed FPs connecting random origin-destination pairs as traffic grows. We describe their shape through effective length, detour (maximum distance of FP from a straight line), inness (signed area between FP and straight line), and their performance through a novel metric measuring how fast and how far an agent travels toward its destination. The entire network is characterized by analyzing the distribution of the performance metric (and its Gini coefficient) across uniformly sampled paths. The study focuses on the traffic loading phenomenon that takes place during the morning peak hour for eight major cities: Networks start with empty edges that are progressively populated by the FPs of single vehicles. As…
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Mobile Agent-Based Network Management · Peer-to-Peer Network Technologies
