Trial and error method for optimal tradable credit schemes: The network case

Xiaolei Wang, Hai Yang, Deren Han, Wei Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)


Recent studies on the new congestion reduction method tradable credit scheme rely on the full information of speed-flow relationship, demand function, and generalized cost. As analytical travel demand, functions are difficult to establish in practice. This paper develops a trial and error method for selecting optimal credit schemes for general networks in the absence of demand functions. After each trial of tradable credit scheme, the credit charging scheme and total amount of credits to be distributed are updated by both observed link flows at traffic equilibrium and revealed credit price at market equilibrium. The updating strategy is based on the method of successive averages and its convergence is established theoretically. Our numerical experiments demonstrate that the method of successive averages based trial and error method for tradable credit schemes has a lower convergence speed in comparison with its counterpart for congestion pricing and could be enhanced by exploring more efficient methods that make full use of credit price information.

Original languageEnglish
Pages (from-to)685-700
Number of pages16
JournalJournal of Advanced Transportation
Issue number6
Publication statusPublished - 1 Oct 2014
Externally publishedYes


  • algorithm
  • convergence
  • equilibrium
  • network
  • tradable credit scheme

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management


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