Futility of being selfish in optimized traffic

Abstract

Optimizing traffic flow is essential for easing congestion. However, even when globally optimal, coordinated, and individualized routes are provided, users may choose alternative routes which offer lower individual costs. By analyzing the impact of selfish route choices on performance using the cavity method, we find that a small ratio of selfish route choices improves the global performance of uncoordinated transportation networks but degrades the efficiency of optimized systems. Remarkably, compliant users always gain in the former and selfish users may gain in the latter, under some parameter conditions. The theoretical results are in good agreement with large-scale simulations. Iterative route switching by a small fraction of selfish users leads to Nash equilibria close to the globally optimal routing solution. Our theoretical framework also generalizes the use of the cavity method, originally developed for the study of equilibrium states, to analyze iterative game-theoretical problems. These results shed light on the feasibility of easing congestion by route coordination when not all vehicles follow the coordinated routes.

Replacement of signalized traffic network design with Hamiltonian roads: delay? Nevermind

“…However, the numerical analysis shows that it is not the case based on the paradox. A recently published paper (Po et al, 2021) shows that sel sh routing degrades the e ciency of the entire network while only a low rate of sel sh drivers achieves their aim. A big part of the drivers takes the sel sh decisions futility.…”

Bilevel Optimization in Flow Networks -- A Message-passing Approach

“…For instance, the MP algorithms can be easily extended to atomic routing games where network flows are discrete variables [40] and are difficult to solve via nonlinear programming. This could potentially be done through the techniques of [41][42][43]. We believe that these MP methods provide a valuable element in the toolbox for solving difficult bilevel optimization problems, especially in systems with sparsely-coupled structures.…”

Scalable node-disjoint and edge-disjoint multiwavelength routing

“…Given that routes are constrained to be contiguous and interaction between paths is non-localized, local optimization methods are insufficient and global optimization is required. Globally optimal routing of multiple messages or vehicles given a general objective function is a computationallyhard constraint satisfaction problems on its own and has been addressed in the physics literature using scalable and distributed message passing approximation techniques, inspired by statistical physics methodology [4][5][6][7]. Moreover, similar techniques have been suggested also for addressing the single-wavelength Node-Disjoint Paths (NDP) [8] and Edge-Disjoint Paths (EDP) [9] problems where multiple paths of different origin-destination pairs cannot share nodes or edges on a graph, respectively.…”