Incorporating multi-level taste heterogeneity in route choice modeling: From disaggregated behavior analysis to aggregated network loading

Dawei Li, Cheng jie Jin, Min Yang, Anthony Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


The aggregated traffic flow forecasting problem with multi-level mixed logit based route choice model is discussed in this paper. Multi-level unobserved taste heterogeneity in route choice is further divided to two parts, the OD pair specific and observation specific. With the proposed model, the observations between the same OD pair, as well as the random utilities between alternative routes are correlated because of sharing the same OD pair specific taste heterogeneity. According to the theoretical analysis, these correlations result in the forecasting errors of aggregated link traffic flow that cannot be ignored as the increasing of number of trips. Numerical studies are carried out to illustrate the quantitative effects of incorporating multi-level taste heterogeneity on disaggregated route choice prediction and aggregated network loading, as well as the effects of model mis-specification on parameter recovery and prediction performance.

Original languageEnglish
Pages (from-to)36-44
Number of pages9
JournalTravel Behaviour and Society
Publication statusPublished - Apr 2020


  • Mixed logit
  • Multi-level model
  • Route choice
  • Stochastic network loading

ASJC Scopus subject areas

  • Transportation

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