Application of variable parking pricing techniques to innovate parking strategies. The case study of Brescia

Abstract

In the last few years in large and medium-sized Italian cities, the motorization index experienced a small reduction compared to its continuous growth in the previous decades for the first time. Furthermore, at the same time, many cities (both Italian and foreign) have set the improvement of public spaces as one of the main objectives of their urban planning strategies, such as removing “on-street” parking to create larger space for pedestrians and social activities. Therefore, management of parking supply and demand has emerged as an important theme.The analysis of some European and American case studies (particularly London, UK, and San Francisco, CA) revealed the existence of innovative plans and actions in urban planning (i.e. the introduction of a maximum standard for parking spaces) and parking strategies (i.e. the implementation of variable parking pricing).Such innovative tools can be considered the starting point of a new parking management optimization process. In particular, the variability of parking pricing in relation to the occupancy index is considered a good method to ensure an “ideal” maximum percentage of occupied parking spaces (ranging between 60% and 80%) mainly in “off-street” parking.This paper firstly aims to provide some guidance for a future application of the performance-based pricing schemes in to the Italian context, based on the results of a recent experiment on variable pricing techniques in San Francisco, California (the “SFpark” programme). This paper wants to encourage the real experimentation in Italy showing with the simulation the potential of this method.Then, this paper describes an Italian case study; the feasibility of potential application of similar techniques was investigated for an off-street parking structure located close to the city centre of Brescia, a medium-sized Italian city, through simulation of the effects that a change in parking fees could have on the occupancy index.