On-street parking management and pricing policies: An evaluation from a system enhancement perspective

Abstract

Abstract Car parking policies often aim to relieve or better distribute parking demand in central urban areas. Evaluating their effectiveness requires the investigation of traveller behaviour and responses to parking attributes such as availability, cost, walking distance, and time restriction. Parking policies, which are usually cost-intensive to implement, are crucial in solving parking problems and transportation system problems in general. To investigate parking policy properly, developing agent-based parking systems is beneficial. Motivated by a recent parking management system designed for Kingsford, Sydney, this paper introduces an agent-based simulation model to analyse the effects of different parking policies in a realistic dynamic framework. Furthermore, a novel behavioural pricing formulation is integrated into the simulation model, which dynamically seeks to maximise the total utility of all agents in the system with consideration of their travel behaviours. The model is implemented for the Kingsford town centre, to investigate the effects of different parking policies and demand scenarios on parking utilisation and system performance.