City Parking Allocations as a Bundle of Society-Aware Deals

It is well recognized that parking in wide and highly populated urban areas is one of the main causes of traffic congestion, air pollution, wasted time, and frustration. In this direction, several initiatives, both from industry and research, are addressing this problem to improve the quality of life for citizens. They usually aim at supporting drivers when selecting parking spaces according to their preferences among competitive alternatives, which are well known in advance to the decision maker, without considering the needs of a city that may impose constraints on the selection process. In this work, an automated software agent negotiation mechanism is used to allocate parking spaces upon drivers requests by trying to accommodate the sometimes conflicting needs coming from the different actors that are involved in a parking allocation process in an urban area. A simulator of the negotiation mechanism is used to globally evaluate the social benefit of the overall allocation problem for a set of parking requests, processed one after another. The obtained results show that negotiation leads in average to an efficient allocations and a better social welfare when compared to baseline cases without negotiation.