Study on modal split method based on nested Logit model

Liya Yao*, Lishan Sun, Hongzhi Guan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

In order to reduce the forecasting error caused by the independence form irrelevant alternatives of traditional model, traffic modals are divided into public traffic and private traffic according to the service objects. Traffic modals that have similar factors are classified into the same arrangement. The nested modal split model is demarcated by the investigational data in Beijing. According to the calculating results, discrete factors that affect arrangement 1 and 2 are in turn the age, have a car or not, pay mode and income, travel aim. Continuous factors are travel time and cost. According to the results, the precision of the model introduced in this paper is high.

Original languageEnglish
Pages (from-to)738-741
Number of pages4
JournalWuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Volume34
Issue number4
DOIs
Publication statusPublished - Aug 2010

Keywords

  • Disaggregated model
  • Forecasting error
  • Modal split
  • Nested Logit model
  • Utility

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