Evaluating Off-Peak Pricing Strategies in Public Transportation with an Activity-Based Approach

Authored by Milan Lovric, Sebastian Raveau, Muhammad Adnan, Kakali Basak, Harish Loganathan, Moshe Ben-Akiva, Francisco C Pereira

Date Published: 2016

DOI: 10.3141/2544-02

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Public transportation authorities across the world are implementing various peak and off-peak pricing strategies to manage travel demand and improve the overall system performance. In this study, an activity-based demand framework was used to evaluate two off-peak pricing strategies currently in use in Singapore. These strategies consisted of a free prepeak travel on mass rapid transit (MRT) and an off-peak discount for an integrated transit (public buses and MRT). Smart card data collected before and after the implementation of the first policy were used to calibrate the behavioral models involved, to capture travelers' preferences and choices properly. To evaluate both pricing strategies, a comprehensive set of key performance indicators was considered and included the changes in peak ridership, average trip fare, operator's revenue, the number of public transportation trips, and mode share. The results indicate that off-peak discount pricing strategies are a viable policy option for spreading demand peaks and that they are more effective during the afternoon peak period. This study also demonstrates the capabilities and the advantages of an agent-based modeling platform, SimMobility, as a tool for policy analysis.

Tags

Congestion time Demand model system