Abstract

The purpose of this study has been the develop of a model for designing an efficient parking pricing policy. The aim is an intelligent control and management system of parking pricing integrated with a redefinition of the circulation scheme for a limited traffic zone in the Central Business District (CBD) of Palermo. The transport demand over the entire area of the town has been studied in order to design various parking pricing scenarios with the application of an additional cost on parking inside the selected area of the CBD. This area attracts most of the private vehicular traffic and it is characterized by university faculties, schools, hospitals, offices and commercial areas. The optimal hourly toll is defined by an iterative maximization process of an objective function. This objective function is subject to the following constraint: the percentage of available parking in the various parking zones has to remain major of the 30%. In this way, the users who need to park close to their final destination can easily find parking. Otherwise it is possible to leave the private car in a “park and ride” area and taking a shuttle bus directed towards the zones of the CBD. A basic principle of this pricing policy is the re-use of revenues for two purposes: to design a shuttle bus service that connects the various “park and ride” areas to the CBD and to improve the local public transport service on the OD pairs that show high travel demand. At the same time it is necessary to eliminate the stop and go flow in cordon roads to increase the capacity and avoid congestion in these critical links. The method shows that in a very simple, and relatively fast, way is possible to get a proposal for the modification of the parking pricing scheme that makes the city center no longer stifled by private car traffic.

Abstract

As traffic congestion gets worse year by year in metropolitan areas, cities search for solutions to improve their traffic performance and reduce their environmental impacts. This paper focuses on parking pricing and congestion pricing and their short-term effects not only on traffic congestion but also on the potential revenue for a city. We develop an easy to implement multimodal macroscopic traffic and parking search model for a central area based on aggregated data at the network level. Our methodology allows us to analyze how introducing parking pricing inside a network, or a congestion toll combined with a park and ride (P+R) scheme can affect the drivers’ decision between entering the network by car (private vehicle) or using P+R instead. This decision directly influences the number of drivers using P+R, and this impacts, in turn, the traffic performance. Based on such analysis, a city can get valuable insights to evaluate whether congestion pricing is a necessity or if the traffic improvements resulting from implementing parking pricing strategies are sufficient when combined with P+R facilities. A search algorithm is used to find the best trade-off between the parking fees and the congestion toll. Any additional revenue collected through these schemes can then be used to improve public transport or the P+R facilities themselves. With minor data collection efforts and little computational costs compared to most existing parking and congestion pricing models, we illustrate our proposed framework in a case study of an area with a high parking demand for public parking spaces within the city of Zurich, Switzerland. Results show that parking pricing combined with P+R is indeed a viable option compared to congestion pricing for improving traffic performance, even if parking pricing schemes do not target all the drivers. Document type: Article