Time-dependent pricing strategies for metro lines considering peak avoidance behaviour of commuters

Abstract

With growing concerns about travel demand management practices in overcrowded metro systems, it is considered that time-dependent pricing strategies are effective for dealing with the crowding occurring during peak commuting hours. In this study, a bi-level optimisation framework is used to consider the peak avoidance behaviour of commuters in the development of time-dependent pricing strategies. The behavioural sensitivity of commuters to pricing factors is investigated in terms of departure time and mode shift decisions based on a stated preference survey conducted in Beijing, China. The proposed bi-level programming model comprises a multi-objective optimisation model at the upper level and a nested logit-based stochastic user equilibrium model at the lower level. Based on an empirical case study of the Batong line in Beijing metro, nine optimal time-dependent pricing strategies are tailored by representative decision preferences, yielding up to 13.97% decrease in the peak ridership during rush hours.

KEYWORDS:

• Differential pricing
• bi-level optimisation
• departure time choice
• mode shift
• nested logit model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Conflict of interest

On behalf of all authors, the corresponding author states that there are no conflicts of interest.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities (2019JBZ107). Stephane Hess acknowledges the support of the European Research Council through the consolidator grant 615596-DECISIONS.