"If only I had taken the other road...": Regret, risk and reinforced learning in informed route-choice

Eran Ben-Elia, Robert Ishaq, Yoram Shiftan

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


This paper presents a study of the effect of regret on route choice behavior when both descriptional information and experiential feedback on choice outcomes are provided. The relevance of Regret Theory in travel behavior has been well demonstrated in non-repeated choice environments involving decisions on the basis of descriptional information. The relation between regret and reinforced learning through experiential feedbacks is less understood. Using data obtained from a simple route-choice experiment involving different levels of travel time variability, discrete-choice models accounting for regret aversion effects are estimated. The results suggest that regret aversion is more evident when descriptional information is provided ex-ante compared to a pure learning from experience condition. Yet, the source of regret is related more strongly to experiential feedbacks rather than to the descriptional information itself. Payoff variability is negatively associated with regret. Regret aversion is more observable in choice situations that reveal risk-seeking, and less in the case of risk-aversion. These results are important for predicting the possible behavioral impacts of emerging information and communication technologies and intelligent transportation systems on travelers' behavior.

Original languageEnglish
Pages (from-to)269-293
Number of pages25
Issue number2
StatePublished - 1 Feb 2013
Externally publishedYes


  • Expected utility
  • Information
  • Intelligent transportation systems
  • Regret
  • Reinforced learning
  • Risk
  • Route-choice

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Development
  • Transportation


Dive into the research topics of '"If only I had taken the other road...": Regret, risk and reinforced learning in informed route-choice'. Together they form a unique fingerprint.

Cite this