A New Tradable Credit Scheme for the Morning Commute Problem

Yu (Marco) Nie*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


This paper seeks to apply a new tradable credit scheme in the morning commute problem. When implementing such a scheme, the congestion management authority first delineates a peak-time window and then requires all traveler who pass the bottleneck within that window to either pay certain units of mobility credits, or a peak time toll (which is comparably more expensive). The authority also rewards credits to anyone who passes the bottleneck during the designated off-peak time window. An artificial market is created so that the travelers may trade these credits with each other. Our analyses, which are based on the Vickrey’s bottleneck model managed by step tolls, indicate that the proposed scheme has several notable advantages. First, the market allows those who value travel time savings less to be directly compensated by selling credits to those who value them more. This mechanism promises simpler and fairer distribution of the benefits from congestion relief. Second, as no transfer of wealth takes places between travelers and the authority, the payment made to acquire credits is less likely to be perceived as a tax. Third, the rewarding-charging mechanism avoids the top-down allocation of credits in existing tradable credit schemes. In the proposed scheme, credits are only rewarded to those who contribute to congestion relief. Last but not least, the proposed scheme is easy to understand and simple to implement. In particular, we show that the best choice of the rewarding-charging ratio is 1, i.e., each peak-time user will be charged one credit and each off-peak user will be awarded one credit.

Original languageEnglish (US)
Pages (from-to)719-741
Number of pages23
JournalNetworks and Spatial Economics
Issue number3
StatePublished - Sep 1 2015


  • Bottleneck model
  • Morning commute problem
  • Step toll
  • Tradable credit scheme

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence


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