Urgency-aware optimal routing in repeated games through artificial currencies

When people choose routes minimizing their individual delay, the aggregate congestion can be much higher compared to that experienced by a centrally-imposed routing. Yet centralized routing is incompatible with presence of self-interested users. How we reconcile two? In this paper address question within repeated game framework and propose fair incentive mechanism based on artificial currencies selfish users in system-optimal fashion, while accounting for temporal preferences. We instantiate parallel-network whereby commute repeatedly (e.g., daily) from common start node end node. Thereafter, focus specific two-arcs case whereby, an currency, are charged when traveling first, fast arc, whilst they rewarded second, slower arc. assume rational model choices through where each user aims at combination today’s discomfort, weighted urgency, average discomfort encountered rest period week). show that, if prices judiciously chosen, pattern converges solution, accommodating users’ urgency. complement our study numerical simulations. Our results it possible achieve solution significantly reducing perceived optimal but urgency-unaware policy.