Forecasting high-speed rail ridership using a simultaneous modeling approach

Rongfang Liu, Andy Li

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The newly launched, June 2009, US High-Speed Intercity Passenger Rail Program has rekindled a renewed interest in forecasting high-speed rail (HSR) ridership. The first step to the concerted effort by the federal, state, rail, and other related agencies to develop a nationwide HSR network is the development of credible approaches to forecast the ridership. This article presents a nested logit/simultaneous choice model to improve the demand forecast in the context of intercity travel. In addition to incorporating the interrelationship between trip generation and mode choice decisions, the simultaneous model also provides a platform for the same utility function flowing between both the decision-making processes. Using American Travel Survey data, supplemented by various mode parameters, the proposed model improves the forecast accuracy and confirms the significant impact of travel costs on both mode choice and trip generation. Furthermore, the cross elasticity of mode choice and trip generation related to travel costs and other modal characteristics may shed some light on transportation policies in the area of intercity travel, especially in anticipation of HSR development.

Original languageEnglish (US)
Pages (from-to)577-590
Number of pages14
JournalTransportation Planning and Technology
Volume35
Issue number5
DOIs
StatePublished - Jul 2012

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Transportation

Keywords

  • elasticity
  • high-speed rail
  • intercity travel choices
  • nested logit model
  • simultaneous model

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