Leveraging Information in Parking Assistance Systems

This paper systematically explores the efficiency of uncoordinated parking space allocation in urban environments with two types of parking facilities. Drivers decide whether to go for inexpensive but limited on-street parking spots or for expensive yet overdimensioned parking lots, incurring an additional cruising cost when they decide for on-street parking spots but fail to actually acquire one. Their decisions are made under perfect knowledge of the total parking supply and costs and different levels of information about the parking demand, i.e., complete/probabilistic information and uncertainty. We take a game-theoretic approach and analyze the parking-space allocation process in each case as resource selection game instances. We derive their equilibria, compute the related price-of-anarchy (PoA) values, and study the impact of pricing on them. It is shown that, under typical pricing policies on the two types of parking facilities, drivers tend to overcompete for the on-street parking space, giving rise to redundant cruising cost. However, this inefficiency can be alleviated through systematic manipulation of the information that is announced to the drivers. In particular, counterintuitive less-is-more effects emerge regarding the way that information availability modulates the resulting efficiency of the process, which underpin general competitive service provision settings.