LAUSR

Smart cities (i.e., cities where the sensing and communication infrastructure is developed enough to offer a central planner an informational advantage over its citizens) make it possible to envision a new kind of congestion alleviation mechanism, in which messages (whether they are they roadside signals or individual path recommendations) are actively and strategically sent to entice drivers to take socially beneficial itineraries. We compare five such information provision strategies—optimal routing, no information available, all information available, public signaling, and personal itinerary recommendation—using a competitive ratio reminiscent of the celebrated price of an anarchy metric, but adapted to stochastic networks. We also define a partial order between information provision policies by saying that a policy is maximally more efficient than another if it is more efficient on all networks and if there are instances for which the inefficiency ratio approaches the deterministic price of anarchy. With these tools, we show that a strict hierarchy exists between all policies, excluding the case of uninformed drivers. The latter is on some networks maximally better than having drivers completely informed, yet arbitrarily inefficient in other instances.