Wardropian Cycles make traffic assignment both optimal and fair by eliminating price-of-anarchy with Cyclical User Equilibrium for compliant connected autonomous vehicles
Micha{\l} Hoffmann, Micha{\l} Bujak, Grzegorz Jamr\'oz, Rafa{\l} Kucharski

TL;DR
This paper introduces Wardropian cycles and Cyclical User Equilibrium to achieve fair and optimal traffic assignment for connected autonomous vehicles, eliminating the price-of-anarchy through cyclical routing strategies.
Contribution
It proposes a novel concept of Wardropian cycles that ensure fairness and optimality in traffic assignment, along with exact and heuristic methods to compute these cycles efficiently.
Findings
Eliminated 670 vehicle-hours of Price-of-Anarchy in Barcelona.
Reduced initial inequity significantly within five days in Berlin.
Less than 7% of initial inequity remains after 10 days in multiple cities.
Abstract
Connected and Autonomous Vehicles (CAVs) open the possibility for centralised routing with full compliance, making System Optimal traffic assignment attainable. However, as System Optimum makes some drivers better off than others, voluntary acceptance seems dubious. To overcome this issue, we propose a new concept of Wardropian cycles, which, in contrast to previous utopian visions, makes the assignment fair on top of being optimal, which amounts to satisfaction of both Wardrop's principles. Such cycles, represented as sequences of permutations to the daily assignment matrices, always exist and equalise, after a limited number of days, average travel times among travellers (like in User Equilibrium) while preserving everyday optimality of path flows (like in System Optimum). We propose exact methods to compute such cycles and reduce their length and within-cycle inconvenience to the…
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