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

A behavioural modelling framework with a dynamic travel strategy path choice approach is presented for unreliable multiservice transit networks. The modelling framework is especially suitable for dynamic run-oriented simulation models that use subjective strategy-based path choice models. After an analysis of the travel strategy approach in unreliable transit networks with the related hyperpaths, the search for the optimal strategy as a Markov decision problem solution is considered. The new modelling framework is then presented and applied to a real network. The paper concludes with an overview of the benefits of the new behavioural framework and outlines scope for further research. Document type: Article