Modelling driver response under road pricing

Abstract

Transportation planners and researchers have for many years been interested in the performance of the Singapore Electronic Road Pricing (ERP) system as a method of relieving congestion. The ERP system is constantly evolving, which calls for explicit models to predict the effects of its changes. Responding to such a need, this study proposes a practical modelling methodology for estimating and forecasting the short-term impacts of ERP introduction and rate adjustment on peak period traffic volumes. For practical purpose, it is proposed to use traffic volume data and transaction data automatically collected by the ERP system in the model calibration and application. Corresponding to the new issues of modelling based on traffic volume and ERP transaction data, several novel approaches are proposed. Separate models are developed for different categories of motorists. The proposed methodology was tested on several roads in Singapore. The results show that this methodology can be applied to a peak period road pricing system with time-variable rates.